| --- |
| library_name: sglang |
| base_model: LiquidAI/LFM2.5-1.2B-Instruct |
| license: other |
| license_name: lfm1.0 |
| license_link: LICENSE |
| pipeline_tag: text-generation |
| tags: |
| - speculative-decoding |
| - dspark |
| - lfm2 |
| - draft-model |
| --- |
| |
| <div align="center"> |
| <img |
| src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png" |
| alt="Liquid AI" |
| style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;" |
| /> |
| <div style="display: flex; justify-content: center; gap: 0.5em; margin-bottom: 1em;"> |
| <a href="https://playground.liquid.ai/"><strong>Try LFM</strong></a> • |
| <a href="https://docs.liquid.ai/lfm/getting-started/welcome"><strong>Docs</strong></a> • |
| <a href="https://leap.liquid.ai/"><strong>LEAP</strong></a> • |
| <a href="https://discord.com/invite/liquid-ai"><strong>Discord</strong></a> |
| </div> |
| </div> |
| |
| # LFM2.5-1.2B-Instruct-DSpark |
|
|
| **LFM2.5-DSpark** is a family of speculative-decoding draft models that adapt DSpark for the LFM2.5 architecture. |
| They allow LFM2.5 models to run faster without degrading quality. |
|
|
| This is a drafter for **[`LiquidAI/LFM2.5-1.2B-Instruct`](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Instruct)**. |
| In SGLang, decoding runs about 2× faster. It also runs on-device on Apple silicon through the Metal backend. |
|
|
| Find more information about LFM2.5-DSpark in our [blog post](https://www.liquid.ai/blog/lfm2.5-dspark). |
|
|
| ## 🗒️ Model Details |
|
|
| LFM2.5-1.2B-Instruct-DSpark is a DSpark speculative-decoding draft model with the following features: |
|
|
| - **Target model**: [`LiquidAI/LFM2.5-1.2B-Instruct`](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Instruct) |
| - **Draft parameters**: **295.7M** (BF16) |
| - **Backbone**: 5 full attention layers, `hidden_size=2048`, `intermediate_size=6144` with SiLU/SwiGLU, GQA with `num_attention_heads=32` / `num_key_value_heads=8`, `head_dim=64` |
| - **Extra heads**: Markov head (rank 256) + confidence head |
| - **Block size**: 9 |
| - **Vocabulary**: 65,536 |
|
|
| Other models in the LFM2.5-DSpark family: |
|
|
| | Drafter | Target | |
| |---|---| |
| | [LFM2.5-1.2B-Instruct-DSpark](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Instruct-DSpark) | [LFM2.5-1.2B-Instruct](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Instruct) | |
| | [LFM2.5-8B-A1B-DSpark](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B-DSpark) | [LFM2.5-8B-A1B](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B) | |
| | [LFM2.5-2.6B-DSpark](https://huggingface.co/LiquidAI/LFM2.5-2.6B-DSpark) | [LFM2.5-2.6B](https://huggingface.co/LiquidAI/LFM2.5-2.6B) | |
|
|
| ## 📊 Performance |
|
|
| ### Benchmarks |
|
|
| Speculative decoding is **exact**: the target verifies every proposed token, so the generated |
| text is what the target would have produced on its own. See [`LiquidAI/LFM2.5-1.2B-Instruct`](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Instruct) for performance benchmarks. |
|
|
| ### Acceptance |
|
|
| Mean accepted tokens per decoding step, by benchmark (1×H100, batch size 1, greedy decoding). |
| Higher means more of the draft's proposed block is accepted per target forward pass, so decoding |
| is faster (at block size 9, the ceiling is 10). |
|
|
| | Benchmark | Accepted tokens / step | |
| |---|---:| |
| | MATH-500 | 5.78 | |
| | GSM8K | 4.25 | |
| | HumanEval | 5.51 | |
| | MBPP | 5.41 | |
| | MT-Bench | 3.11 | |
| | **Mean** | **4.81** | |
|
|
| ### On-device and GPU Inference |
|
|
| | Dataset | Acceptance (of 10\) | Speedup on H100 | Speedup on M4 Max | |
| | :---- | :---- | :---- | :---- | |
| | MATH500 | 6.02 | **2.56x**<br/>668 → 1712 tok/s | **2.62x**<br/>140 → 366 tok/s | |
| | HumanEval | 5.31 | **2.26x**<br/>664 → 1499 tok/s | **2.87x**<br/>136 → 389 tok/s | |
| | MBPP | 5.52 | **2.37x**<br/>667 → 1578 tok/s | **2.74x**<br/>137 → 375 tok/s | |
| | GSM8K | 4.34 | **1.67x**<br/>624 → 1041 tok/s | **2.73x**<br/>140 → 381 tok/s | |
| | MT-Bench | 3.90 | **1.66x**<br/>657 → 1091 tok/s | **1.72x**<br/>137 → 237 tok/s | |
| | Mean | 5.02 | **2.10x**<br/>656 → 1384 tok/s | **2.54x**<br/>138 → 350 tok/s | |
|
|
| ## 🏃 How to run (SGLang) |
|
|
| Requires a build of SGLang with DSpark support for LFM2 targets |
| ([PR #31041](https://github.com/sgl-project/sglang/pull/31041)). Launch the target with the drafter |
| attached: |
|
|
| ```bash |
| python -m sglang.launch_server \ |
| --model-path LiquidAI/LFM2.5-1.2B-Instruct \ |
| --speculative-algorithm DSPARK \ |
| --speculative-draft-model-path LiquidAI/LFM2.5-1.2B-Instruct-DSpark \ |
| --speculative-draft-attention-backend flashinfer \ |
| --disable-radix-cache --mem-fraction-static 0.75 --port 30000 |
| ``` |
|
|
| Then query the OpenAI-compatible endpoint at `http://localhost:30000/v1`. The block size is read |
| from the draft's `config.json`; the baseline is the same command without the three |
| `--speculative-*` flags. |
|
|
| ## 📬 Contact |
|
|
| - Got questions or want to connect? [Join our Discord community](https://discord.com/invite/liquid-ai) |
| - If you are interested in custom solutions with edge deployment, please contact [our sales team](https://www.liquid.ai/contact). |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{liquidAI202626B, |
| author = {Liquid AI}, |
| title = {LFM2.5-2.6B: Agents Everywhere}, |
| journal = {Liquid AI Blog}, |
| year = {2026}, |
| note = {www.liquid.ai/blog/lfm2-5-2-6b}, |
| } |
| ``` |
|
|
| ```bibtex |
| @article{liquidAI2026dspark, |
| author = {Liquid AI}, |
| title = {LFM2.5-DSpark: Up to 3.2x Faster Inference from H100 to MacBook}, |
| journal = {Liquid AI Blog}, |
| year = {2026}, |
| note = {www.liquid.ai/blog/lfm2.5-dspark}, |
| } |
| ``` |
|
|
