GPT-5.1 Codex mini vs Mistral Large 3 vs Qwen3-Next 80B-A3B Instruct
GPT-5.1 Codex mini comes out ahead, 59 to 50 and 39 on our weighted score, and it is the cheaper option too.
- Our pick
OpenAIGPT-5.1 Codex mini
59/100- ECI—
- Price$0.25 / $2.00
- Context400K
Mistral AIMistral Large 3
50/100- ECI—
- Price$0.50 / $1.50
- Context262K
Alibaba (Qwen)Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- Context131K
GPT-5.1 Codex mini is our pick
GPT-5.1 Codex mini is the better all-round choice, scoring 59/100 against Mistral Large 3 (50) and Qwen3-Next 80B-A3B Instruct (39). It leads on price, inputs & features and context window. 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 priceGPT-5.1 Codex miniGPT-5.1 Codex mini $0.688 · Mistral Large 3 $0.75 · Qwen3-Next 80B-A3B Instruct $0.875 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1 Codex miniGPT-5.1 Codex mini 400,000 · Mistral Large 3 262,144 · Qwen3-Next 80B-A3B Instruct 131,072 tokens
- Widest inputsGPT-5.1 Codex mini and Mistral Large 3GPT-5.1 Codex mini: Text, Images · Mistral Large 3: Text, Images · Qwen3-Next 80B-A3B Instruct: Text
- Self-hostingMistral Large 3 and Qwen3-Next 80B-A3B InstructPublishes downloadable weights
| Measure | Weight | GPT-5.1 Codex mini | Mistral Large 3 | Qwen3-Next 80B-A3B Instruct |
|---|---|---|---|---|
| Price | 50% | 58 | 56 | 53 |
| Inputs & features | 30% | 70 | 50 | 25 |
| Context window | 20% | 44 | 37 | 24 |
| Overall | 100% | 59/100 | 50/100 | 39/100 |
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 | GPT-5.1 Codex miniOpenAI | Mistral Large 3Mistral AI | Qwen3-Next 80B-A3B InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.25 (best) | $0.50 | $0.50 |
| Output | $2.00 | $1.50 (best) | $2.00 |
| Cached input | — | $0.05 | — |
| Blended (3:1) | $0.688 (best) | $0.75 | $0.875 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 10 providers | Official Mistral API | Official Alibaba API |
| Limits | |||
| Context window | 400,000 tokens (best) | 262,144 tokens | 131,072 tokens |
| Max output | 128,000 tokens | 262,144 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | — | mistral-large-2512 | qwen3-next-80b-a3b-instruct |
| API providers | 10 | 13 (best) | 13 (best) |
| Released | Nov 13, 2025 | Dec 2, 2025 | Sep 2025 |
| Knowledge cutoff | Sep 30, 2024 | Nov 2024 | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-5.1 Codex mini$6.50
- Mistral Large 3$8.00
- Qwen3-Next 80B-A3B Instruct$9.00
Which should you choose?
Which is better: GPT-5.1 Codex mini, Mistral Large 3 or Qwen3-Next 80B-A3B Instruct?
GPT-5.1 Codex mini is the better all-round choice, scoring 59/100 against Mistral Large 3 (50) and Qwen3-Next 80B-A3B Instruct (39). It leads on price, inputs & features and context window. 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-5.1 Codex mini, Mistral Large 3 or Qwen3-Next 80B-A3B Instruct?
GPT-5.1 Codex mini is cheaper at $0.25 input / $2.00 output per million tokens (median across 10 API providers). Mistral Large 3 costs $0.50 input / $1.50 output per million tokens (official Mistral API price); Qwen3-Next 80B-A3B Instruct costs $0.50 input / $2.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.688 per million tokens for GPT-5.1 Codex mini versus $0.75 for Mistral Large 3 (1.1× as much) and $0.875 for Qwen3-Next 80B-A3B Instruct (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.1 Codex mini has not been scored yet, Mistral Large 3 has not been scored yet and Qwen3-Next 80B-A3B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.1 Codex mini, Mistral Large 3 and Qwen3-Next 80B-A3B Instruct 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?
GPT-5.1 Codex mini has the largest context window at 400,000 tokens, against 262,144 for Mistral Large 3 and 131,072 for Qwen3-Next 80B-A3B Instruct. Maximum output per response: GPT-5.1 Codex mini up to 128,000, Mistral Large 3 up to 262,144, Qwen3-Next 80B-A3B Instruct up to 32,768 tokens.
Which can read images, PDFs, audio or video?
GPT-5.1 Codex mini accepts text and images; Mistral Large 3 accepts text and images; Qwen3-Next 80B-A3B Instruct accepts text. GPT-5.1 Codex mini handles the widest range of inputs.
Are any of these open source?
Mistral Large 3 and Qwen3-Next 80B-A3B Instruct publishes its weights and can be self-hosted; GPT-5.1 Codex mini is proprietary.
Which is newer?
Mistral Large 3 is the newest, released Dec 2, 2025. GPT-5.1 Codex mini came out Nov 13, 2025; Qwen3-Next 80B-A3B Instruct came out Sep 2025. Knowledge cutoff: GPT-5.1 Codex mini Sep 30, 2024, Mistral Large 3 Nov 2024, Qwen3-Next 80B-A3B Instruct Apr 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.
