GLM-4.7-FlashX vs GPT-5.1 Codex mini vs Mistral Large 3
Too close to call on our weighted score (GLM-4.7-FlashX 61, GPT-5.1 Codex mini 59, Mistral Large 3 50). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.7-FlashX
61/100- ECI—
- Price$0.07 / $0.40
- Context200K
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
Too close to call
It is close. Our weighted score puts them within 3 points (GLM-4.7-FlashX 61/100, GPT-5.1 Codex mini 59/100, Mistral Large 3 50/100), so choose by what matters most for your work: GLM-4.7-FlashX 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 priceGLM-4.7-FlashXGLM-4.7-FlashX $0.152 · GPT-5.1 Codex mini $0.688 · Mistral Large 3 $0.75 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1 Codex miniGPT-5.1 Codex mini 400,000 · Mistral Large 3 262,144 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsGPT-5.1 Codex mini and Mistral Large 3GLM-4.7-FlashX: Text · GPT-5.1 Codex mini: Text, Images · Mistral Large 3: Text, Images
- Self-hostingGLM-4.7-FlashX and Mistral Large 3Publishes downloadable weights
| Measure | Weight | GLM-4.7-FlashX | GPT-5.1 Codex mini | Mistral Large 3 |
|---|---|---|---|---|
| Price | 50% | 89 | 58 | 56 |
| Inputs & features | 30% | 35 | 70 | 50 |
| Context window | 20% | 32 | 44 | 37 |
| Overall | 100% | 61/100 | 59/100 | 50/100 |
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 | GLM-4.7-FlashXZ.ai (Zhipu) | GPT-5.1 Codex miniOpenAI | Mistral Large 3Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.07 (best) | $0.25 | $0.50 |
| Output | $0.40 (best) | $2.00 | $1.50 |
| Cached input | $0.01 (best) | — | $0.05 |
| Blended (3:1) | $0.152 (best) | $0.688 | $0.75 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 10 providers | Official Mistral API |
| Limits | |||
| Context window | 200,000 tokens | 400,000 tokens (best) | 262,144 tokens |
| Max output | 131,072 tokens | 128,000 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | glm-4.7-flashx | — | mistral-large-2512 |
| API providers | 8 | 10 | 13 (best) |
| Released | Jan 19, 2026 | Nov 13, 2025 | Dec 2, 2025 |
| Knowledge cutoff | Apr 2025 | Sep 30, 2024 | Nov 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-4.7-FlashX$1.50
- GPT-5.1 Codex mini$6.50
- Mistral Large 3$8.00
Which should you choose?
Which is better: GLM-4.7-FlashX, GPT-5.1 Codex mini or Mistral Large 3?
It is close. Our weighted score puts them within 3 points (GLM-4.7-FlashX 61/100, GPT-5.1 Codex mini 59/100, Mistral Large 3 50/100), so choose by what matters most for your work: GLM-4.7-FlashX 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, GLM-4.7-FlashX, GPT-5.1 Codex mini or Mistral Large 3?
GLM-4.7-FlashX is cheaper at $0.07 input / $0.40 output per million tokens (official Z.AI API price). GPT-5.1 Codex mini costs $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). At a typical mix of three input tokens to one output token, that is $0.152 per million tokens for GLM-4.7-FlashX versus $0.688 for GPT-5.1 Codex mini (4.5× as much) and $0.75 for Mistral Large 3 (4.9× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.7-FlashX has not been scored yet, GPT-5.1 Codex mini has not been scored yet and Mistral Large 3 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7-FlashX, GPT-5.1 Codex mini and Mistral Large 3 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 200,000 for GLM-4.7-FlashX. Maximum output per response: GLM-4.7-FlashX up to 131,072, GPT-5.1 Codex mini up to 128,000, Mistral Large 3 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7-FlashX accepts text; GPT-5.1 Codex mini accepts text and images; Mistral Large 3 accepts text and images. GPT-5.1 Codex mini handles the widest range of inputs.
Are any of these open source?
GLM-4.7-FlashX and Mistral Large 3 publishes its weights and can be self-hosted; GPT-5.1 Codex mini is proprietary.
Which is newer?
GLM-4.7-FlashX is the newest, released Jan 19, 2026. Mistral Large 3 came out Dec 2, 2025; GPT-5.1 Codex mini came out Nov 13, 2025. Knowledge cutoff: GLM-4.7-FlashX Apr 2025, GPT-5.1 Codex mini Sep 30, 2024, Mistral Large 3 Nov 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.
