GPT OSS 120B vs Voxtral Small 24B 2507 vs Qwen3 235B-A22B Instruct 2507
Too close to call on our weighted score (GPT OSS 120B 57, Voxtral Small 24B 2507 55, Qwen3 235B-A22B Instruct 2507 52). The right pick depends on what you value most.
OpenAI
GPT OSS 120B
57/100- ECI140.0
- Price$0.15 / $0.60
- Context131K
Mistral AI
Voxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.30
- Context33K
Alibaba (Qwen)
Qwen3 235B-A22B Instruct 2507
52/100- ECI138.9
- Price$0.15 / $0.75
- Context262K
Too close to call
It is close. Our weighted score puts them within 2 points (GPT OSS 120B 57/100, Voxtral Small 24B 2507 55/100, Qwen3 235B-A22B Instruct 2507 52/100), so choose by what matters most for your work: Voxtral Small 24B 2507 on price and Qwen3 235B-A22B Instruct 2507 for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceVoxtral Small 24B 2507Voxtral Small 24B 2507 $0.15 · GPT OSS 120B $0.263 · Qwen3 235B-A22B Instruct 2507 $0.30 per 1M tokens (3:1 blend)
- Longest contextQwen3 235B-A22B Instruct 2507Qwen3 235B-A22B Instruct 2507 262,144 · GPT OSS 120B 131,072 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsVoxtral Small 24B 2507GPT OSS 120B: Text · Voxtral Small 24B 2507: Text, Audio · Qwen3 235B-A22B Instruct 2507: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GPT OSS 120B | Voxtral Small 24B 2507 | Qwen3 235B-A22B Instruct 2507 |
|---|---|---|---|---|
| Price | 50% | 77 | 89 | 75 |
| Inputs & features | 30% | 45 | 35 | 25 |
| Context window | 20% | 24 | 0 | 37 |
| Overall | 100% | 57/100 | 55/100 | 52/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 140.0 (best) | — | 138.9 |
| ECI rank | #99 of 148 (best) | — | #105 of 148 |
| GPQA DiamondGraduate-level science questions | 75.8% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 88.9% | — | — |
| Price per million tokens | |||
| Input | $0.15 | $0.10 (best) | $0.15 |
| Output | $0.60 | $0.30 (best) | $0.75 |
| Cached input | — | — | — |
| Blended (3:1) | $0.263 | $0.15 (best) | $0.30 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 36 providers | Official Mistral API | Median of 11 providers |
| Limits | |||
| Context window | 131,072 tokens | 32,768 tokens | 262,144 tokens (best) |
| Max output | 32,768 tokens (best) | 32,768 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | OpenApache 2.0 | OpenApache 2.0 |
| API model ID | — | voxtral-small-latest | — |
| API providers | 39 (best) | 7 | 11 |
| Released | Aug 5, 2025 | Jul 15, 2025 | Jul 21, 2025 |
| Knowledge cutoff | — | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
GPT OSS 120B$2.70
Voxtral Small 24B 2507$1.60
Qwen3 235B-A22B Instruct 2507$3.00
Which should you choose?
Which is better: GPT OSS 120B, Voxtral Small 24B 2507 or Qwen3 235B-A22B Instruct 2507?
It is close. Our weighted score puts them within 2 points (GPT OSS 120B 57/100, Voxtral Small 24B 2507 55/100, Qwen3 235B-A22B Instruct 2507 52/100), so choose by what matters most for your work: Voxtral Small 24B 2507 on price and Qwen3 235B-A22B Instruct 2507 for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GPT OSS 120B, Voxtral Small 24B 2507 or Qwen3 235B-A22B Instruct 2507?
Voxtral Small 24B 2507 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). GPT OSS 120B costs $0.15 input / $0.60 output per million tokens (median across 36 API providers); Qwen3 235B-A22B Instruct 2507 costs $0.15 input / $0.75 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Voxtral Small 24B 2507 versus $0.263 for GPT OSS 120B (1.8× as much) and $0.30 for Qwen3 235B-A22B Instruct 2507 (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT OSS 120B has an ECI of 140.0, Voxtral Small 24B 2507 has not been scored yet and Qwen3 235B-A22B Instruct 2507 has an ECI of 138.9.
Which is better for coding?
There are no published SWE-bench Verified results for GPT OSS 120B, Voxtral Small 24B 2507 and Qwen3 235B-A22B Instruct 2507 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3 235B-A22B Instruct 2507 has the largest context window at 262,144 tokens, against 131,072 for GPT OSS 120B and 32,768 for Voxtral Small 24B 2507. Maximum output per response: GPT OSS 120B up to 32,768, Voxtral Small 24B 2507 up to 32,768, Qwen3 235B-A22B Instruct 2507 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
GPT OSS 120B accepts text; Voxtral Small 24B 2507 accepts text and audio; Qwen3 235B-A22B Instruct 2507 accepts text. Voxtral Small 24B 2507 handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
GPT OSS 120B is the newest, released Aug 5, 2025. Qwen3 235B-A22B Instruct 2507 came out Jul 21, 2025; Voxtral Small 24B 2507 came out Jul 15, 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.