Dataset Viewer
Auto-converted to Parquet Duplicate
test
stringclasses
2 values
tool
stringclasses
2 values
model
stringclasses
4 values
mcp_tools
int64
0
30
run
int64
1
5
input_tokens
int64
14.6k
124k
cached_input_tokens
float64
29.8k
95.5k
⌀
output_tokens
float64
2.87k
8.54k
⌀
seconds
float64
33
75
⌀
api_cost_usd
float64
0.35
0.42
⌀
file_lines
float64
29
527
⌀
startup
claude_code
claude-opus-5-5 (default, Max plan)
0
1
35,765
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
0
2
35,777
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
0
3
35,781
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
0
4
35,781
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
1
1
35,790
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
1
2
35,790
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
1
3
35,794
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
1
4
35,794
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
10
1
35,913
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
10
2
35,913
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
10
3
35,917
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
10
4
35,917
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
30
1
36,165
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
30
2
36,165
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
30
3
36,169
null
null
null
null
null
startup
claude_code
claude-opus-5-5 (default, Max plan)
30
4
36,169
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
0
1
14,678
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
0
2
14,678
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
0
3
15,018
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
0
4
14,618
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
1
1
14,678
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
1
2
14,678
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
1
3
14,618
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
1
4
14,618
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
10
1
14,678
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
10
2
14,678
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
10
3
14,618
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
10
4
14,618
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
30
1
14,678
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
30
2
14,678
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
30
3
14,618
null
null
null
null
null
startup
codex
gpt-6-luna, reasoning effort low (ChatGPT plan)
30
4
14,618
null
null
null
null
null
same_task
claude_code
claude-opus-5-5, effort medium
0
1
123,666
95,504
8,537
73
0.42
487
same_task
claude_code
claude-opus-5-5, effort medium
0
2
79,213
51,762
7,870
63
0.39
527
same_task
codex
gpt-6-luna, reasoning effort medium
0
1
47,954
29,824
2,872
33
null
49
same_task
codex
gpt-6-luna, reasoning effort medium
0
2
48,815
37,504
3,803
41
null
117
same_task
claude_code
claude-opus-5-5, effort medium
0
3
79,316
51,766
7,897
62
0.39
513
same_task
claude_code
claude-opus-5-5, effort medium
0
4
77,868
51,766
6,595
52
0.35
421
same_task
claude_code
claude-opus-5-5, effort medium
0
5
78,830
51,766
7,447
60
0.38
420
same_task
codex
gpt-6-luna, reasoning effort medium
0
3
70,704
60,032
7,118
75
null
29
same_task
codex
gpt-6-luna, reasoning effort medium
0
4
48,362
37,248
3,468
72
null
46
same_task
codex
gpt-6-luna, reasoning effort medium
0
5
47,975
37,248
3,103
57
null
51

Claude Code vs Codex: startup tokens, MCP tools and the same coding task

Input tokens Claude Code and Codex use before doing any work, what adding 1 to 30 MCP tools adds, and tokens, time and output for the same browser-game task at medium effort.

Headline: a one-word reply costs 35,776 input tokens in Claude Code (Opus 5.5) and 14,748 in Codex (gpt-6-luna). On the same coding task Codex used 40% fewer input tokens and 47% fewer output tokens (5 runs each). Adding 30 MCP tools barely changed either.

Key findings

  • Claude Code starts 143% heavier: 35,776 vs 14,748 (average of 4 runs) input tokens for a one-word reply. That fixed amount is sent with every request (mostly cached).
  • Adding MCP tools barely changed startup tokens. The full definitions of our 30 test tools are 4,541 tokens, but adding them raised Claude Code by 391 tokens (about 13 per tool) and Codex by nothing measurable. Both load a tool's details only when needed.
  • Using the tools is what costs: asked to list the 10 test tools and call one, Codex used 47,876 input tokens (+225% over its plain startup).
  • Same task, fewer tokens on Codex: Claude Code averaged 87,779 input and 7,669 output tokens (62 s, $0.39 at API prices); Codex 52,762 input and 4,073 output tokens (56 s). All 10 games worked.
  • Claude Code wrote more code: 474 lines on average vs 58 for Codex, which wrote denser code.

Files

  • claude-code-vs-codex-tokens.csv: one row per run with test (startup or same_task), tool, model, mcp_tools, run, input_tokens, cached_input_tokens, output_tokens, seconds, api_cost_usd, file_lines
  • claude-code-vs-codex-tokens.json: the same data plus prompts and setup
  • mcp_dummy.js: the test MCP server (node mcp_dummy.js <number_of_tools>)

Startup tokens and MCP tools (average of 2 runs)

Setup Claude Code (Opus 5.5) Codex (gpt-6-luna)
0 MCP tools 35,776 14,748
1 MCP tool 35,792 (+16) 14,648 (-100)
10 MCP tools 35,915 (+139) 14,648 (-100)
30 MCP tools 36,167 (+391) 14,648 (-100)

The same coding task

Prompt: "Make a brick-breaker game that runs in the browser as a single file named index.html in the current folder. It needs 2 levels, a score display and 3 lives, and it must be playable with the keyboard and the mouse. Write the file and finish."

Run Input tokens Output tokens Time Lines API cost
Claude Code · run 1 123,666 8,537 73 s 487 $0.42
Claude Code · run 2 79,213 7,870 63 s 527 $0.39
Codex · run 1 47,954 2,872 33 s 49 –
Codex · run 2 48,815 3,803 41 s 117 –
Claude Code · run 3 (2026-10-22) 79,316 7,897 62 s 513 $0.39
Claude Code · run 4 77,868 6,595 52 s 421 $0.35
Claude Code · run 5 78,830 7,447 60 s 420 $0.38
Codex · run 3 (2026-10-22) 70,704 7,118 75 s 29 –
Codex · run 4 48,362 3,468 72 s 46 –
Codex · run 5 47,975 3,103 57 s 51 –

Method

  1. Both tools on the same Windows laptop, each run in its own empty folder.
  2. Claude Code 2.1.295, default model Opus 5.5, Max plan: claude -p --output-format json, MCP servers only from --mcp-config with --strict-mcp-config; task at --effort medium --permission-mode acceptEdits. Input = input + cache creation + cache read tokens; cost is Claude Code's API-price figure.
  3. Codex CLI 0.162, default model gpt-6-luna, ChatGPT plan: codex exec --json, reasoning effort low (startup) and medium (task); MCP server via -c mcp_servers.…. Input tokens include cached tokens; no price on a ChatGPT plan.
  4. Every game was opened in a headless browser: no errors, two levels, score and three lives on screen.

Limitations

  • Four startup and five task runs per tool, one task. One Claude Code task run took an extra step (123,666 input tokens) and one Codex run read 70,704.
  • Default models and per-token prices differ, so fewer tokens is not automatically cheaper.
  • Startup tokens include each tool's installed skills and plugins on this machine.
  • Cursor will be added when its free-plan limit resets.

Citation

TokenSave (2026). Claude Code vs Codex: startup tokens, MCP tools and the same coding task [Data set]. Zenodo. https://doi.org/10.5281/zenodo.23448342

See your own Claude Code and Codex usage at tokensave.app.

Downloads last month
78