Qwen Flash vs GPT-5.1 Codex mini vs Voxtral Small 24B 2507
Qwen Flash comes out ahead, 68 to 59 and 55 on our weighted score, and it is the cheaper option too.
- Our pick
Alibaba (Qwen)Qwen Flash
68/100- ECI—
- Price$0.05 / $0.40
- Context1M
OpenAIGPT-5.1 Codex mini
59/100- ECI—
- Price$0.25 / $2.00
- Context400K
Mistral AIVoxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.30
- Context33K
Qwen Flash is our pick
Qwen Flash is the better all-round choice, scoring 68/100 against GPT-5.1 Codex mini (59) and Voxtral Small 24B 2507 (55). It leads on price and context window. GPT-5.1 Codex mini wins on inputs & features. 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 priceQwen FlashQwen Flash $0.138 · Voxtral Small 24B 2507 $0.15 · GPT-5.1 Codex mini $0.688 per 1M tokens (3:1 blend)
- Longest contextQwen FlashQwen Flash 1,000,000 · GPT-5.1 Codex mini 400,000 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsGPT-5.1 Codex mini and Voxtral Small 24B 2507Qwen Flash: Text · GPT-5.1 Codex mini: Text, Images · Voxtral Small 24B 2507: Text, Audio
- Self-hostingVoxtral Small 24B 2507Publishes downloadable weights (Apache 2.0)
| Measure | Weight | Qwen Flash | GPT-5.1 Codex mini | Voxtral Small 24B 2507 |
|---|---|---|---|---|
| Price | 50% | 91 | 58 | 89 |
| Inputs & features | 30% | 35 | 70 | 35 |
| Context window | 20% | 60 | 44 | 0 |
| Overall | 100% | 68/100 | 59/100 | 55/100 |
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 | Qwen FlashAlibaba (Qwen) | GPT-5.1 Codex miniOpenAI | Voxtral Small 24B 2507Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.25 | $0.10 |
| Output | $0.40 | $2.00 | $0.30 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.138 (best) | $0.688 | $0.15 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 10 providers | Official Mistral API |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 400,000 tokens | 32,768 tokens |
| Max output | 32,768 tokens | 128,000 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | No | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | OpenApache 2.0 |
| API model ID | qwen-flash | — | voxtral-small-latest |
| API providers | 6 | 10 (best) | 7 |
| Released | Jul 28, 2025 | Nov 13, 2025 | Jul 15, 2025 |
| Knowledge cutoff | Apr 2024 | Sep 30, 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen Flash$1.30
- GPT-5.1 Codex mini$6.50
- Voxtral Small 24B 2507$1.60
Which should you choose?
Which is better: Qwen Flash, GPT-5.1 Codex mini or Voxtral Small 24B 2507?
Qwen Flash is the better all-round choice, scoring 68/100 against GPT-5.1 Codex mini (59) and Voxtral Small 24B 2507 (55). It leads on price and context window. GPT-5.1 Codex mini wins on inputs & features. 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, Qwen Flash, GPT-5.1 Codex mini or Voxtral Small 24B 2507?
Qwen Flash is cheaper at $0.05 input / $0.40 output per million tokens (official Alibaba API price). Voxtral Small 24B 2507 costs $0.10 input / $0.30 output per million tokens (official Mistral API price); GPT-5.1 Codex mini costs $0.25 input / $2.00 output per million tokens (median across 10 API providers). At a typical mix of three input tokens to one output token, that is $0.138 per million tokens for Qwen Flash versus $0.15 for Voxtral Small 24B 2507 (1.1× as much) and $0.688 for GPT-5.1 Codex mini (5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen Flash has not been scored yet, GPT-5.1 Codex mini has not been scored yet and Voxtral Small 24B 2507 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen Flash, GPT-5.1 Codex mini and Voxtral Small 24B 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?
Qwen Flash has the largest context window at 1,000,000 tokens, against 400,000 for GPT-5.1 Codex mini and 32,768 for Voxtral Small 24B 2507. Maximum output per response: Qwen Flash up to 32,768, GPT-5.1 Codex mini up to 128,000, Voxtral Small 24B 2507 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen Flash accepts text; GPT-5.1 Codex mini accepts text and images; Voxtral Small 24B 2507 accepts text and audio. GPT-5.1 Codex mini handles the widest range of inputs.
Are any of these open source?
Voxtral Small 24B 2507 publishes its weights (Apache 2.0) and can be self-hosted; Qwen Flash and GPT-5.1 Codex mini is proprietary.
Which is newer?
GPT-5.1 Codex mini is the newest, released Nov 13, 2025. Qwen Flash came out Jul 28, 2025; Voxtral Small 24B 2507 came out Jul 15, 2025. Knowledge cutoff: Qwen Flash Apr 2024, GPT-5.1 Codex mini Sep 30, 2024.
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.
