GLM-5 vs Mistral Medium 3.5
Too close to call on our weighted score (GLM-5 55, Mistral Medium 3.5 55). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-5
55/100- ECI145.8
- Price$1.00 / $3.20
- Context205K
Mistral AIMistral Medium 3.5
55/100- ECI141.4
- Price$1.50 / $7.50
- Context262K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (GLM-5 55/100, Mistral Medium 3.5 55/100), so choose by what matters most for your work: GLM-5 for raw capability and Mistral Medium 3.5 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-5Capabilities Index (ECI): GLM-5 145.8 · Mistral Medium 3.5 141.4
- Lowest priceGLM-5GLM-5 $1.55 · Mistral Medium 3.5 $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Medium 3.5Mistral Medium 3.5 262,144 · GLM-5 204,800 tokens
- Widest inputsMistral Medium 3.5GLM-5: Text · Mistral Medium 3.5: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-5 | Mistral Medium 3.5 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 73 | 67 |
| Price | 25% | 41 | 27 |
| Inputs & features | 15% | 35 | 70 |
| Context window | 10% | 32 | 37 |
| Overall | 100% | 55/100 | 55/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5Z.ai (Zhipu) | Mistral Medium 3.5Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 145.8 (best) | 141.4 |
| ECI rank | #74 of 148 (best) | #95 of 148 |
| GPQA DiamondGraduate-level science questions | 87.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 80.0% | — |
| SWE-bench VerifiedFixing real GitHub issues | 72.1% | — |
| Price per million tokens | ||
| Input | $1.00 (best) | $1.50 |
| Output | $3.20 (best) | $7.50 |
| Cached input | $0.20 | $0.15 (best) |
| Blended (3:1) | $1.55 (best) | $3.00 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Mistral API |
| Limits | ||
| Context window | 204,800 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 | Yeshigh |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Open | Open |
| API model ID | glm-5 | mistral-medium-2604 |
| API providers | 27 (best) | 12 |
| Released | Feb 12, 2026 | Apr 29, 2026 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5$16.40
- Mistral Medium 3.5$30.00
Which should you choose?
Which is better: GLM-5 or Mistral Medium 3.5?
It is close. Our weighted score puts them within a point (GLM-5 55/100, Mistral Medium 3.5 55/100), so choose by what matters most for your work: GLM-5 for raw capability and Mistral Medium 3.5 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5 or Mistral Medium 3.5?
GLM-5 is cheaper at $1.00 input / $3.20 output per million tokens (official Z.AI API price). Mistral Medium 3.5 costs $1.50 input / $7.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $1.55 per million tokens for GLM-5 versus $3.00 for Mistral Medium 3.5 (1.9× as much).
Which scores higher on benchmarks?
GLM-5 scores higher on the Capabilities Index (ECI): GLM-5 145.8 (#74 of 148) and Mistral Medium 3.5 141.4 (#95 of 148). Their confidence ranges do not overlap (143.9–147.7 vs 138.4–143.7), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Medium 3.5 yet, so there is no like-for-like coding score. On overall capability, GLM-5 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Mistral Medium 3.5 has the largest context window at 262,144 tokens, against 204,800 for GLM-5. Maximum output per response: GLM-5 up to 131,072, Mistral Medium 3.5 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GLM-5 accepts text; Mistral Medium 3.5 accepts text and images. Mistral Medium 3.5 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?
Mistral Medium 3.5 is the newest, released Apr 29, 2026. GLM-5 came out Feb 12, 2026.
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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