Mistral Large 3 vs Seed 2.0 Pro vs GPT-5.1 Codex mini
Too close to call on our weighted score (GPT-5.1 Codex mini 59, Seed 2.0 Pro 57, Mistral Large 3 50). The right pick depends on what you value most.
Mistral AI
Mistral Large 3
50/100- ECI—
- Price$0.50 / $1.50
- Context262K
ByteDance Seed
Seed 2.0 Pro
57/100- ECI—
- Price$0.475 / $2.37
- Context256K
OpenAI
GPT-5.1 Codex mini
59/100- ECI—
- Price$0.25 / $2.00
- Context400K
Too close to call
It is close. Our weighted score puts them within 2 points (GPT-5.1 Codex mini 59/100, Seed 2.0 Pro 57/100, Mistral Large 3 50/100), so choose by what matters most for your work: GPT-5.1 Codex mini on price and GPT-5.1 Codex mini 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 priceGPT-5.1 Codex miniGPT-5.1 Codex mini $0.688 · Mistral Large 3 $0.75 · Seed 2.0 Pro $0.95 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1 Codex miniGPT-5.1 Codex mini 400,000 · Mistral Large 3 262,144 · Seed 2.0 Pro 256,000 tokens
- Widest inputsSeed 2.0 ProMistral Large 3: Text, Images · Seed 2.0 Pro: Text, Images, Video · GPT-5.1 Codex mini: Text, Images
- Self-hostingMistral Large 3Publishes downloadable weights
| Measure | Weight | Mistral Large 3 | Seed 2.0 Pro | GPT-5.1 Codex mini |
|---|---|---|---|---|
| Price | 50% | 56 | 51 | 58 |
| Inputs & features | 30% | 50 | 80 | 70 |
| Context window | 20% | 37 | 36 | 44 |
| Overall | 100% | 50/100 | 57/100 | 59/100 |
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) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 | $0.475 | $0.25 (best) |
| Output | $1.50 (best) | $2.37 | $2.00 |
| Cached input | $0.05 (best) | $0.095 | — |
| Blended (3:1) | $0.75 | $0.95 | $0.688 (best) |
| Long-context rate | Same rate | Over 32K: $0.712 / $3.56 | Same rate |
| Price source | Official Mistral API | Official Volcengine Ark API | Median of 10 providers |
| Limits | |||
| Context window | 262,144 tokens | 256,000 tokens | 400,000 tokens (best) |
| Max output | 262,144 tokens (best) | 128,000 tokens | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | No | Yesminimal · low · medium · high · xhigh · max | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | mistral-large-2512 | doubao-seed-2-0-pro-260215 | — |
| API providers | 13 (best) | 5 | 10 |
| Released | Dec 2, 2025 | Feb 14, 2026 | Nov 13, 2025 |
| Knowledge cutoff | Nov 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.
Mistral Large 3$8.00
Seed 2.0 Pro$9.50
GPT-5.1 Codex mini$6.50
Which should you choose?
Which is better: Mistral Large 3, Seed 2.0 Pro or GPT-5.1 Codex mini?
It is close. Our weighted score puts them within 2 points (GPT-5.1 Codex mini 59/100, Seed 2.0 Pro 57/100, Mistral Large 3 50/100), so choose by what matters most for your work: GPT-5.1 Codex mini on price and GPT-5.1 Codex mini 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, Mistral Large 3, Seed 2.0 Pro or GPT-5.1 Codex mini?
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); Seed 2.0 Pro costs $0.475 input / $2.37 output per million tokens (official Volcengine Ark 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 $0.95 for Seed 2.0 Pro (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Mistral Large 3 has not been scored yet, Seed 2.0 Pro has not been scored yet and GPT-5.1 Codex mini has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large 3, Seed 2.0 Pro and GPT-5.1 Codex mini 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 256,000 for Seed 2.0 Pro. Maximum output per response: Mistral Large 3 up to 262,144, Seed 2.0 Pro up to 128,000, GPT-5.1 Codex mini up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Mistral Large 3 accepts text and images; Seed 2.0 Pro accepts text, images and video; GPT-5.1 Codex mini accepts text and images. Seed 2.0 Pro handles the widest range of inputs.
Are any of these open source?
Mistral Large 3 publishes its weights and can be self-hosted; Seed 2.0 Pro and GPT-5.1 Codex mini is proprietary.
Which is newer?
Seed 2.0 Pro is the newest, released Feb 14, 2026. Mistral Large 3 came out Dec 2, 2025; GPT-5.1 Codex mini came out Nov 13, 2025. Knowledge cutoff: Mistral Large 3 Nov 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.