Vision Large vs GLM-4.5-Flash vs Codestral
Vision Large comes out ahead, 84 to 31 and 29 on our weighted score.
- Our pick
VisparkVision Large
84/100- ECI—
- Price—
- Context1M
Z.ai (Zhipu)GLM-4.5-Flash
31/100- ECI—
- PriceFree / Free
- Context131K
Mistral AICodestral
29/100- ECI—
- Price$0.30 / $0.90
- Context256K
Vision Large is our pick
Vision Large is the better all-round choice, scoring 84/100 against GLM-4.5-Flash (31) and Codestral (29). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. 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 · Codestral $0.45 per 1M tokens (3:1 blend) · Vision Large unpriced
- Longest contextVision LargeVision Large 1,000,000 · Codestral 256,000 · GLM-4.5-Flash 131,072 tokens
- Widest inputsVision LargeVision Large: Text, Images, PDFs, Audio, Video · GLM-4.5-Flash: Text · Codestral: Text
- Self-hostingCodestralPublishes downloadable weights
| Measure | Weight | Vision Large | GLM-4.5-Flash | Codestral |
|---|---|---|---|---|
| Inputs & features | 60% | 100 | 35 | 25 |
| Context window | 40% | 60 | 24 | 36 |
| Overall | 100% | 84/100 | 31/100 | 29/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Vision LargeVispark | GLM-4.5-FlashZ.ai (Zhipu) | CodestralMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | Free (best) | $0.30 |
| Output | — | Free (best) | $0.90 |
| Cached input | — | — | $0.03 |
| Blended (3:1) | — | Free (best) | $0.45 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official Z.AI API | Official Mistral API |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 131,072 tokens | 256,000 tokens |
| Max output | 65,536 tokens | 98,304 tokens (best) | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | — | glm-4.5-flash | codestral-latest |
| API providers | — | 4 (best) | 3 |
| Released | May 15, 2024 | Jul 28, 2025 | May 29, 2024 |
| Knowledge cutoff | — | Apr 2025 | Oct 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Vision Large—
- GLM-4.5-FlashFree
- Codestral$4.80
Which should you choose?
Which is better: Vision Large, GLM-4.5-Flash or Codestral?
Vision Large is the better all-round choice, scoring 84/100 against GLM-4.5-Flash (31) and Codestral (29). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Vision Large, GLM-4.5-Flash or Codestral?
GLM-4.5-Flash is cheaper at Free input / Free output per million tokens (official Z.AI API price). Codestral costs $0.30 input / $0.90 output per million tokens (official Mistral API price). GLM-4.5-Flash is listed as free. Vision Large has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Vision Large has not been scored yet, GLM-4.5-Flash has not been scored yet and Codestral has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Vision Large, GLM-4.5-Flash and Codestral 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?
Vision Large has the largest context window at 1,000,000 tokens, against 256,000 for Codestral and 131,072 for GLM-4.5-Flash. Maximum output per response: Vision Large up to 65,536, GLM-4.5-Flash up to 98,304, Codestral up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Vision Large accepts text, images, PDFs, audio and video; GLM-4.5-Flash accepts text; Codestral accepts text. Vision Large handles the widest range of inputs.
Are any of these open source?
Codestral publishes its weights and can be self-hosted; Vision Large and GLM-4.5-Flash is proprietary.
Which is newer?
GLM-4.5-Flash is the newest, released Jul 28, 2025. Codestral came out May 29, 2024; Vision Large came out May 15, 2024. Knowledge cutoff: GLM-4.5-Flash Apr 2025, Codestral Oct 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.
