GLM-4.7-FlashX vs Mistral Large 3
GLM-4.7-FlashX comes out ahead, 61 to 50 on our weighted score, and it is the cheaper option too.
- Our pick
Z.ai (Zhipu)GLM-4.7-FlashX
61/100- ECI—
- Price$0.07 / $0.40
- Context200K
Mistral AIMistral Large 3
50/100- ECI—
- Price$0.50 / $1.50
- Context262K
Add a model
Make it a three-way comparison.
GLM-4.7-FlashX is our pick
GLM-4.7-FlashX is the better all-round choice, scoring 61/100 against Mistral Large 3 (50). It leads on price. Mistral Large 3 wins on 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 priceGLM-4.7-FlashXGLM-4.7-FlashX $0.152 · Mistral Large 3 $0.75 per 1M tokens (3:1 blend)
- Longest contextMistral Large 3Mistral Large 3 262,144 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsMistral Large 3GLM-4.7-FlashX: Text · Mistral Large 3: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-4.7-FlashX | Mistral Large 3 |
|---|---|---|---|
| Price | 50% | 89 | 56 |
| Inputs & features | 30% | 35 | 50 |
| Context window | 20% | 32 | 37 |
| Overall | 100% | 61/100 | 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) | Mistral Large 3Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.07 (best) | $0.50 |
| Output | $0.40 (best) | $1.50 |
| Cached input | $0.01 (best) | $0.05 |
| Blended (3:1) | $0.152 (best) | $0.75 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Mistral API |
| Limits | ||
| Context window | 200,000 tokens | 262,144 tokens (best) |
| Max output | 131,072 tokens | 262,144 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | glm-4.7-flashx | mistral-large-2512 |
| API providers | 8 | 13 (best) |
| Released | Jan 19, 2026 | Dec 2, 2025 |
| Knowledge cutoff | Apr 2025 | 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
- Mistral Large 3$8.00
Which should you choose?
Which is better: GLM-4.7-FlashX or Mistral Large 3?
GLM-4.7-FlashX is the better all-round choice, scoring 61/100 against Mistral Large 3 (50). It leads on price. Mistral Large 3 wins on 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, GLM-4.7-FlashX 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). 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 $0.75 for Mistral Large 3 (4.9× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-4.7-FlashX 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 and Mistral Large 3 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Mistral Large 3 has the largest context window at 262,144 tokens, against 200,000 for GLM-4.7-FlashX. Maximum output per response: GLM-4.7-FlashX up to 131,072, Mistral Large 3 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7-FlashX accepts text; Mistral Large 3 accepts text and images. Mistral Large 3 handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
GLM-4.7-FlashX is the newest, released Jan 19, 2026. Mistral Large 3 came out Dec 2, 2025. Knowledge cutoff: GLM-4.7-FlashX Apr 2025, 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.
