GLM-4.5-Air vs Voxtral Small 24B 2507 vs Codestral 25.08
Voxtral Small 24B 2507 comes out ahead, 55 to 48 and 47 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-4.5-Air
48/100- ECI—
- Price$0.20 / $1.10
- Context131K
- Our pick
Mistral AIVoxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.40
- Context33K
- Mistral AI
Codestral 25.08
47/100- ECI—
- Price$0.30 / $0.90
- Context128K
Voxtral Small 24B 2507 is our pick
Voxtral Small 24B 2507 is the better all-round choice, scoring 55/100 against GLM-4.5-Air (48) and Codestral 25.08 (47). It leads on price and inputs & features. 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 priceVoxtral Small 24B 2507Voxtral Small 24B 2507 $0.175 · GLM-4.5-Air $0.425 · Codestral 25.08 $0.45 per 1M tokens (3:1 blend)
- Longest contextGLM-4.5-AirGLM-4.5-Air 131,072 · Codestral 25.08 128,000 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsVoxtral Small 24B 2507GLM-4.5-Air: Text · Voxtral Small 24B 2507: Text, Audio · Codestral 25.08: Text
- Self-hostingGLM-4.5-Air and Voxtral Small 24B 2507Publishes downloadable weights (Apache 2.0)
| Measure | Weight | GLM-4.5-Air | Voxtral Small 24B 2507 | Codestral 25.08 |
|---|---|---|---|---|
| Price | 50% | 65 | 82 | 64 |
| Inputs & features | 30% | 35 | 45 | 35 |
| Context window | 20% | 25 | 0 | 24 |
| Overall | 100% | 48/100 | 55/100 | 47/100 |
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-AirZ.ai (Zhipu) | Voxtral Small 24B 2507Mistral AI | Codestral 25.08Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.10 (best) | $0.30 |
| Output | $1.10 | $0.40 (best) | $0.90 |
| Cached input | $0.03 | — | $0.03 |
| Blended (3:1) | $0.425 | $0.175 (best) | $0.45 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Mistral API | Official Mistral API |
| Limits | |||
| Context window | 131,072 tokens (best) | 32,768 tokens | 128,000 tokens |
| Max output | 98,304 tokens (best) | 32,768 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Proprietary |
| API model ID | glm-4.5-air | voxtral-small-latest | codestral-2508 |
| API providers | 19 (best) | 10 | 11 |
| Released | Jul 28, 2025 | Jul 15, 2025 | Jul 30, 2025 |
| Knowledge cutoff | Apr 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-Air$4.20
- Voxtral Small 24B 2507$1.80
- Codestral 25.08$4.80
Which should you choose?
Which is better: GLM-4.5-Air, Voxtral Small 24B 2507 or Codestral 25.08?
Voxtral Small 24B 2507 is the better all-round choice, scoring 55/100 against GLM-4.5-Air (48) and Codestral 25.08 (47). It leads on price and inputs & features. 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-Air, Voxtral Small 24B 2507 or Codestral 25.08?
Voxtral Small 24B 2507 is cheaper at $0.10 input / $0.40 output per million tokens (official Mistral API price). GLM-4.5-Air costs $0.20 input / $1.10 output per million tokens (official Z.AI API price); Codestral 25.08 costs $0.30 input / $0.90 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for Voxtral Small 24B 2507 versus $0.425 for GLM-4.5-Air (2.4× as much) and $0.45 for Codestral 25.08 (2.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.5-Air has not been scored yet, Voxtral Small 24B 2507 has not been scored yet and Codestral 25.08 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5-Air, Voxtral Small 24B 2507 and Codestral 25.08 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?
GLM-4.5-Air has the largest context window at 131,072 tokens, against 128,000 for Codestral 25.08 and 32,768 for Voxtral Small 24B 2507. Maximum output per response: GLM-4.5-Air up to 98,304, Voxtral Small 24B 2507 up to 32,768, Codestral 25.08 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Air accepts text; Voxtral Small 24B 2507 accepts text and audio; Codestral 25.08 accepts text. Voxtral Small 24B 2507 handles the widest range of inputs.
Are any of these open source?
GLM-4.5-Air and Voxtral Small 24B 2507 publishes its weights (Apache 2.0) and can be self-hosted; Codestral 25.08 is proprietary.
Which is newer?
Codestral 25.08 is the newest, released Jul 30, 2025. GLM-4.5-Air came out Jul 28, 2025; Voxtral Small 24B 2507 came out Jul 15, 2025. Knowledge cutoff: GLM-4.5-Air Apr 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 Nov 2, 2026.
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