GLM-4.5V vs Ling-1T vs Mistral Medium 3.1
Too close to call on our weighted score (Mistral Medium 3.1 50, GLM-4.5V 49, Ling-1T 37). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.5V
49/100- ECI—
- Price$0.60 / $1.80
- Context64K
inclusionAILing-1T
37/100- ECI—
- Price$0.57 / $2.29
- Context128K
Mistral AIMistral Medium 3.1
50/100- ECI—
- Price$0.40 / $2.00
- Context262K
Too close to call
It is close. Our weighted score puts them within a point (Mistral Medium 3.1 50/100, GLM-4.5V 49/100, Ling-1T 37/100), so choose by what matters most for your work: Mistral Medium 3.1 on price and Mistral Medium 3.1 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 priceMistral Medium 3.1Mistral Medium 3.1 $0.80 · GLM-4.5V $0.90 · Ling-1T $1.00 per 1M tokens (3:1 blend)
- Longest contextMistral Medium 3.1Mistral Medium 3.1 262,144 · Ling-1T 128,000 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VGLM-4.5V: Text, Images, Video · Ling-1T: Text · Mistral Medium 3.1: Text, Images
- Self-hostingGLM-4.5V and Ling-1TPublishes downloadable weights
| Measure | Weight | GLM-4.5V | Ling-1T | Mistral Medium 3.1 |
|---|---|---|---|---|
| Price | 50% | 52 | 50 | 54 |
| Inputs & features | 30% | 70 | 25 | 50 |
| Context window | 20% | 12 | 24 | 37 |
| Overall | 100% | 49/100 | 37/100 | 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-4.5VZ.ai (Zhipu) | Ling-1TinclusionAI | Mistral Medium 3.1Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.60 | $0.57 | $0.40 (best) |
| Output | $1.80 (best) | $2.29 | $2.00 |
| Cached input | — | — | — |
| Blended (3:1) | $0.90 | $1.00 | $0.80 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Bailing API | Official Mistral API |
| Limits | |||
| Context window | 64,000 tokens | 128,000 tokens | 262,144 tokens (best) |
| Max output | 16,384 tokens | 32,000 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-4.5v | Ling-1T | mistral-medium-2508 |
| API providers | 11 (best) | 1 | 1 |
| Released | Aug 11, 2025 | Oct 2025 | Aug 12, 2025 |
| Knowledge cutoff | Apr 2025 | Jun 2024 | May 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-4.5V$9.60
- Ling-1T$10.28
- Mistral Medium 3.1$8.00
Which should you choose?
Which is better: GLM-4.5V, Ling-1T or Mistral Medium 3.1?
It is close. Our weighted score puts them within a point (Mistral Medium 3.1 50/100, GLM-4.5V 49/100, Ling-1T 37/100), so choose by what matters most for your work: Mistral Medium 3.1 on price and Mistral Medium 3.1 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-4.5V, Ling-1T or Mistral Medium 3.1?
Mistral Medium 3.1 is cheaper at $0.40 input / $2.00 output per million tokens (official Mistral API price). GLM-4.5V costs $0.60 input / $1.80 output per million tokens (official Z.AI API price); Ling-1T costs $0.57 input / $2.29 output per million tokens (official Bailing API price). At a typical mix of three input tokens to one output token, that is $0.80 per million tokens for Mistral Medium 3.1 versus $0.90 for GLM-4.5V (1.1× as much) and $1.00 for Ling-1T (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.5V has not been scored yet, Ling-1T has not been scored yet and Mistral Medium 3.1 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5V, Ling-1T and Mistral Medium 3.1 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?
Mistral Medium 3.1 has the largest context window at 262,144 tokens, against 128,000 for Ling-1T and 64,000 for GLM-4.5V. Maximum output per response: GLM-4.5V up to 16,384, Ling-1T up to 32,000, Mistral Medium 3.1 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5V accepts text, images and video; Ling-1T accepts text; Mistral Medium 3.1 accepts text and images. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
GLM-4.5V and Ling-1T publishes its weights and can be self-hosted; Mistral Medium 3.1 is proprietary.
Which is newer?
Ling-1T is the newest, released Oct 2025. Mistral Medium 3.1 came out Aug 12, 2025; GLM-4.5V came out Aug 11, 2025. Knowledge cutoff: GLM-4.5V Apr 2025, Ling-1T Jun 2024, Mistral Medium 3.1 May 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.
