Hugging Face's logo

MiniMaxAI
/
MiniMax-M3.1-Flash

Image-Text-to-Text
Transformers
Safetensors
minimax_m3_vl
multimodal
Mixture of Experts
agent
coding
video
conversational
custom_code
Eval Results
8-bit precision
mxfp8
Model card Files
xet
 Community
6
MiniMax-M3.1-Flash
File size: 23,760 Bytes
54e4e69
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
---
pipeline_tag: image-text-to-text
license: other
license_name: minimax-community
license_link: LICENSE
library_name: transformers
tags:
  - multimodal
  - moe
  - agent
  - coding
  - video
---

<div align="center">
  <img width="60%" src="figures/logo.svg" alt="MiniMax">
</div>
<hr>

<p align="center">
  <a href="https://agent.minimax.io/" target="_blank"><img src="https://img.shields.io/badge/MiniMax%20Agent-FF6C37?logo=minimax&logoColor=white" alt="MiniMax Agent"></a>
  <a href="https://platform.minimax.io/docs/guides/text-generation" target="_blank"><img src="https://img.shields.io/badge/API-FF6C37?logo=minimax&logoColor=white" alt="API"></a>
  <a href="https://www.minimax.io" target="_blank"><img src="https://img.shields.io/badge/MiniMax%20Website-FF6C37?logo=minimax&logoColor=white" alt="MiniMax Website"></a>
  <br>
  <a href="https://modelscope.cn/organization/minimax" target="_blank" rel="noopener noreferrer"><img alt="ModelScope MiniMax AI" src="https://img.shields.io/badge/ModelScope-MiniMax%20AI-white?labelColor=%23EF3D5D"></a>
  <a href="https://platform.minimaxi.com/docs/faq/contact-us" target="_blank"><img src="https://img.shields.io/badge/WeChat-07C160?logo=wechat&logoColor=white" alt="WeChat"></a>
  <a href="https://discord.com/invite/DPC4AHFCBw" target="_blank"><img src="https://img.shields.io/badge/Discord-5865F2?logo=discord&logoColor=white" alt="Discord"></a>
  <a href="https://huggingface.co/MiniMaxAI" target="_blank"><img src="https://img.shields.io/badge/Hugging%20Face-FFD21E?logo=huggingface&logoColor=black" alt="Hugging Face"></a>
  <a href="https://github.com/MiniMax-AI" target="_blank"><img src="https://img.shields.io/badge/GitHub-181717?logo=github&logoColor=white" alt="GitHub"></a>
  <a href="https://arxiv.org/abs/2606.13392" target="_blank"><img src="https://img.shields.io/badge/arXiv-2606.13392-B31B1B?logo=arxiv&logoColor=white" alt="arXiv Paper"></a>
</p>

**MiniMax-M3.1-Flash** is a native multimodal mixture-of-experts model for coding, agentic workflows, computer use, and cybersecurity. It supports text, image, and video inputs with a context window of up to **1M tokens**.

Building on MiniMax-M3, M3.1-Flash improves task performance and inference efficiency with sparse attention throughout the model, quantization-aware training, and DSpark speculative decoding.

**Highlights:**
- **Agentic performance:** A generational leap in agentic tasks, coding, and cybersecurity — 76.2 on BankerToolBench, 73.7% on DeepSWE v1.1, 61.7 on OSWorld V2, 29.6 on Agents' Last Exam, and 82.2 on CyberGym.
- **Efficient by design:** Sparse attention throughout, quantization-aware training, and DSpark speculative decoding improve inference efficiency.


## Model at a Glance

- **Architecture:** Native multimodal mixture-of-experts (MoE)
- **Parameters:** Approximately 428B total; 23B activated per token
- **Inputs / output:** Text, image, and video inputs; text output
- **Context window:** Up to 1,000,000 tokens
- **Attention:** [MiniMax Sparse Attention](https://arxiv.org/abs/2606.13392) (MSA) throughout the model
- **Speculative decoding:** DSpark draft head included

## Benchmarks

<div style="overflow-x:auto;margin:16px 0">
<table style="width:100%;border-collapse:collapse;font-size:14px">
<thead>
<tr>
<th style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;font-weight:600;border-bottom:2px solid #f25f5c;background:#f7f7f8;">Benchmark</th>
<th style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;font-weight:600;border-bottom:2px solid #f25f5c;background:rgba(242,95,92,0.08);">MiniMax M3.1 Flash</th>
<th style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;font-weight:600;border-bottom:2px solid #f25f5c;background:#f7f7f8;">DeepSeek V4.1 Flash-1017</th>
<th style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;font-weight:600;border-bottom:2px solid #f25f5c;background:#f7f7f8;">DeepSeek V4.1 Flash</th>
<th style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;font-weight:600;border-bottom:2px solid #f25f5c;background:#f7f7f8;">Kimi K3</th>
<th style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;font-weight:600;border-bottom:2px solid #f25f5c;background:#f7f7f8;">GLM-5.3</th>
<th style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;font-weight:600;border-bottom:2px solid #f25f5c;background:#f7f7f8;">GPT-5.6 Sol</th>
<th style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;font-weight:600;border-bottom:2px solid #f25f5c;background:#f7f7f8;">Opus 5</th>
</tr>
</thead>
<tbody>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;"><div>Automation-Bench v1.0.6</div></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);"><strong>62.8</strong></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">60.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">54.8</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">46.7</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">48.8</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">45.8</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">50.3</td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;">BankerToolBench</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);"><strong>76.2</strong></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">73.7</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">69.1</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">74.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">74.6</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;"><strong>76.2</strong></td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;">GDP.pdf AA</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);">20.8</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">12.8</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">22.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">11.2</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;"><strong>27.2</strong></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">21.6</td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;">Terminal Bench 4.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);">38.1</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">42.3</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">31.2</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">12.6</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">37.9</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">39.9</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;"><strong>51.8</strong></td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;">LOCA-Bench 256K</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);"><strong>60.3</strong></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">49.7</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">50.3</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">60.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">53.7</td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;"><div>Agents’ Last Exam</div></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;background:rgba(242,95,92,0.08);">29.6</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">28.3</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">30.6</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;"><strong>32.2</strong></td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;">OSWorld 2.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);">61.7</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">54.3</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">58.3</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">65.7</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;"><strong>70.6</strong></td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;"><div>PostTrain Bench v1.1</div></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;background:rgba(242,95,92,0.08);">39.3</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">30.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">36.6</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">37.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">36.2</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;"><strong>40.4</strong></td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;">DeepSWE v1.1</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);">73.7</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;"><strong>77.0</strong></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">74.2</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">67.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">66.9</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">73.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">74.0</td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;">NL2Repo-Bench</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);">61.2</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">68.2</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">65.4</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">58.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">58.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">56.8</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;"><strong>75.3</strong></td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;">SWE Refactor Bench</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);">23.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">11.8</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">19.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">10.4</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">28.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;"><strong>31.0</strong></td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;"><div>CyberGym</div></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;background:rgba(242,95,92,0.08);">82.2</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">80.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;"><strong>84.5</strong></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">83.6</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">—</td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;"><div>BabyVision (with tools)</div></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;background:rgba(242,95,92,0.08);">91.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">92.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">89.6</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">85.7</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;">88.9</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;border-top:2px solid #f1d6d3;"><strong>94.1</strong></td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;">HLE (without tools)</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);">43.4</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">42.6</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">39.2</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">43.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">42.3</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">49.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;"><strong>55.6</strong></td>
</tr>
<tr>
<td style="padding:10px 12px;text-align:left;vertical-align:middle;border-bottom:1px solid #e5e7eb;">CharXiv RQ</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;background:rgba(242,95,92,0.08);">82.5</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">69.0</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">84.8</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">—</td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;"><strong>85.2</strong></td>
<td style="padding:10px 12px;text-align:center;vertical-align:middle;border-bottom:1px solid #e5e7eb;">83.7</td>
</tr>
</tbody>
</table>
</div>

<details>
<summary><strong>Evaluation Notes</strong></summary>

- **Automation-Bench v1.0.6:** 600 publicly released tasks.
- **BankerToolBench:** OpenCode 1.17.18; MiniMax-M2.7 judge.
- **GDP.pdf AA:** Taken directly from Artificial Analysis.
- **Terminal Bench 4.0:** Codex 0.149.1.
- **LOCA-Bench 256K:** Official implementation.
- **Agents’ Last Exam:** Official Overall setting; full-set results from the official ALE leaderboard only. Blank = no official result (CLI-only excluded), not zero.
- **OSWorld 2.0:** 0808 Full release; highest reported per model at release, except DeepSeek V4.1 (in-house reproduction).
- **PostTrain Bench v1.1:** Claude Code 2.1.251, 512K context; otherwise official setup.
- **DeepSWE v1.1:** mini-SWE-agent 2.4.5, 512K context.
- **NL2Repo-Bench:** Claude Code 2.1.233, 512K context; reward hacking = 0; two inconsistent tasks corrected (scores use the corrected set).
- **SWE Refactor Bench:** Claude Code 2.1.220, 200K context; otherwise official setup.
- **CyberGym:** Claude Code 2.1.263, 1M context.
- **BabyVision (with tools):** Claude Code 2.1.285; min image side 1,500 px.
- **HLE (without tools):** Text-only subset (2,158 questions).
- **CharXiv RQ:** GPT-5.5 judge.

</details>

Results are for the official weights; third-party quantizations may differ.

## What’s New in M3.1-Flash

M3.1-Flash retains M3’s core mixture-of-experts architecture, with three main changes:

- **Sparse attention throughout:** the first three full-attention layers are replaced with sparse attention.
- **Quantization-aware training:** the routed MoE experts and the attention paths are quantized during training, reducing memory footprint and improving serving efficiency.
- **DSpark speculative decoding:** DSpark replaces the earlier EAGLE-like MTP approach. The release includes the draft head for use with compatible serving implementations.


## How to Use

- [MiniMax Agent](https://agent.minimax.io/)
- [MiniMax API](https://platform.minimax.io/)

### Local Deployment

Download the model:

```bash
hf download MiniMaxAI/MiniMax-M3.1-Flash --local-dir MiniMax-M3.1-Flash
```

We recommend the following inference frameworks to serve the model:

- [SGLang](https://docs.sglang.io/) — see [SGLang cookbook](https://docs.sglang.io/cookbook/autoregressive/MiniMax/MiniMax-M3.1).
- [vLLM](https://github.com/vllm-project/vllm) — see [vLLM recipe](https://recipes.vllm.ai/MiniMaxAI/MiniMax-M3.1-Flash).
- [TokenSpeed](https://github.com/lightseekorg/tokenspeed) — see [TokenSpeed recipe](https://lightseek.org/tokenspeed/recipes/models#minimax-m3-1).

Additional integrations in progress: Transformers, KTransformers, unsloth, and ATOM.

### Multi-Chip Deployment

[FlagOS](https://github.com/flagos-ai) — see [Multi-Chip Support and Downloads](https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash/blob/main/docs/FlagOS-Multi-Chip-Support-and-Downloads.md).

## Inference Settings

Recommended sampling settings: `temperature=1.0` and `top_p=0.95`.

For reasoning, set `reasoning_effort` in the chat template: `low`, `medium`, `high`, `xhigh`, or `max`.

The model supports a context window of up to 1M tokens. Usable context length and throughput depend on GPU memory and the serving configuration.

## Contact Us

Contact us at [model@minimax.io](mailto:model@minimax.io).