GPT-5.1-Codex-Max vs Voxtral Small 24B 2507
Voxtral Small 24B 2507 costs 33.3x less per output token than GPT-5.1-Codex-Max ($0.30 vs $10.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $10.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.30
GPT-5.1-Codex-Max or Voxtral Small 24B 2507: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.1-Codex-Max for a larger context window (400K against 33K tokens).
No benchmark has tested both yet. GPT-5.1-Codex-Max has results on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench; Voxtral Small 24B 2507 has none yet. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Long documents
Listed context window
GPT-5.1-Codex-Max
GPT-5.1-Codex-Max takes 400K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Voxtral Small 24B 2507
GPT-5.1-Codex-Max $0.0063, Voxtral Small 24B 2507 $0.0003 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Max not benchmarked, Voxtral Small 24B 2507 not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-5.1-Codex-Max $10.00 against Voxtral Small 24B 2507 $0.30 per million output tokens, 33.3x apart.
- Context window
- GPT-5.1-Codex-Max takes 400K tokens, Voxtral Small 24B 2507 33K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
| Benchmark | GPT-5.1-Codex-Max | Voxtral Small 24B 2507 | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | 83.6% | Not measured | Only GPT-5.1-Codex-Max measured |
| Vibe Code Bench (Vals AI) | 22.2% | Not measured | Only GPT-5.1-Codex-Max measured |
| Terminal-Bench | 60.4% | Not measured | Only GPT-5.1-Codex-Max measured |
| ALE-Bench | 1228.3 | Not measured | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 35 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.1-Codex-Max | Voxtral Small 24B 2507 | Leader |
|---|---|---|---|
| METR time horizons | 70.8% | Not measured | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 40 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.1-Codex-Max | Voxtral Small 24B 2507 | Leader |
|---|---|---|---|
| ProofBench | 9.0% | Not measured | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 12 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Voxtral Small 24B 2507 costs less
Repository review
50K input + 3K output tokens
Voxtral Small 24B 2507 costs less
Agent loop
200K input + 10K output tokens
Voxtral Small 24B 2507 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-5.1-Codex-Max | Mistral Voxtral Small 24B 2507 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | December 4, 2025 | October 30, 2025 |
| Context window | 400K | 33K |
| Input $/Mtok | $1.25 | $0.10 |
| Output $/Mtok | $10.00 | $0.30 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex-Max better than Voxtral Small 24B 2507 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Max for a larger context window (400K against 33K tokens).
Which is cheaper, GPT-5.1-Codex-Max or Voxtral Small 24B 2507?
GPT-5.1-Codex-Max costs $1.25 per million input tokens and $10.00 per million output tokens; Voxtral Small 24B 2507 costs $0.10 and $0.30. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.1-Codex-Max or Voxtral Small 24B 2507?
GPT-5.1-Codex-Max, with 400K tokens against 33K.
Has any benchmark tested both GPT-5.1-Codex-Max and Voxtral Small 24B 2507?
No benchmark has tested both yet. GPT-5.1-Codex-Max has results on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench; Voxtral Small 24B 2507 has none yet. Compare them on price and context instead. Data as of October 21, 2026.