GLM-4.5-Flash vs Mistral Small 3.2
Too close to call on our weighted score (GLM-4.5-Flash 65, Mistral Small 3.2 64). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.5-Flash
65/100- ECI—
- PriceFree / Free
- Context131K
Mistral AIMistral Small 3.2
64/100- ECI131.7
- Price$0.10 / $0.30
- Context128K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 1 points (GLM-4.5-Flash 65/100, Mistral Small 3.2 64/100), so choose by what matters most for your work: GLM-4.5-Flash on price and GLM-4.5-Flash 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-4.5-FlashGLM-4.5-Flash Free · Mistral Small 3.2 $0.15 per 1M tokens (3:1 blend)
- Longest contextGLM-4.5-FlashGLM-4.5-Flash 131,072 · Mistral Small 3.2 128,000 tokens
- Widest inputsMistral Small 3.2GLM-4.5-Flash: Text · Mistral Small 3.2: Text, Images
- Self-hostingMistral Small 3.2Publishes downloadable weights
| Measure | Weight | GLM-4.5-Flash | Mistral Small 3.2 |
|---|---|---|---|
| Price | 50% | 100 | 89 |
| Inputs & features | 30% | 35 | 50 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 65/100 | 64/100 |
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-4.5-FlashZ.ai (Zhipu) | Mistral Small 3.2Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 131.7 |
| ECI rank | — | #123 of 148 |
| GPQA DiamondGraduate-level science questions | — | 49.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 30.3% |
| Price per million tokens | ||
| Input | Free (best) | $0.10 |
| Output | Free (best) | $0.30 |
| Cached input | — | — |
| Blended (3:1) | Free (best) | $0.15 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Mistral API |
| Limits | ||
| Context window | 131,072 tokens (best) | 128,000 tokens |
| Max output | 98,304 tokens (best) | 16,384 tokens |
| 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 | Proprietary | Open |
| API model ID | glm-4.5-flash | mistral-small-2506 |
| API providers | 4 | 6 (best) |
| Released | Jul 28, 2025 | Jun 20, 2025 |
| Knowledge cutoff | Apr 2025 | Mar 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-4.5-FlashFree
- Mistral Small 3.2$1.60
Which should you choose?
Which is better: GLM-4.5-Flash or Mistral Small 3.2?
It is close. Our weighted score puts them within 1 points (GLM-4.5-Flash 65/100, Mistral Small 3.2 64/100), so choose by what matters most for your work: GLM-4.5-Flash on price and GLM-4.5-Flash 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-4.5-Flash or Mistral Small 3.2?
GLM-4.5-Flash is cheaper at Free input / Free output per million tokens (official Z.AI API price). Mistral Small 3.2 costs $0.10 input / $0.30 output per million tokens (official Mistral API price). GLM-4.5-Flash is listed as free.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-4.5-Flash has not been scored yet and Mistral Small 3.2 has an ECI of 131.7.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5-Flash and Mistral Small 3.2 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?
GLM-4.5-Flash has the largest context window at 131,072 tokens, against 128,000 for Mistral Small 3.2. Maximum output per response: GLM-4.5-Flash up to 98,304, Mistral Small 3.2 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Flash accepts text; Mistral Small 3.2 accepts text and images. Mistral Small 3.2 handles the widest range of inputs.
Are any of these open source?
Mistral Small 3.2 publishes its weights and can be self-hosted; GLM-4.5-Flash is proprietary.
Which is newer?
GLM-4.5-Flash is the newest, released Jul 28, 2025. Mistral Small 3.2 came out Jun 20, 2025. Knowledge cutoff: GLM-4.5-Flash Apr 2025, Mistral Small 3.2 Mar 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.
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