GLM-4.5-Air vs Hermes 2 Pro Llama 3 8B vs Codestral 25.08
Hermes 2 Pro Llama 3 8B comes out ahead, 51 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
Nous ResearchHermes 2 Pro Llama 3 8B
51/100- ECI—
- Price$0.14 / $0.14
- Context8K
Mistral AICodestral 25.08
47/100- ECI—
- Price$0.30 / $0.90
- Context128K
Hermes 2 Pro Llama 3 8B is our pick
Hermes 2 Pro Llama 3 8B is the better all-round choice, scoring 51/100 against GLM-4.5-Air (48) and Codestral 25.08 (47). It leads on price. 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 priceHermes 2 Pro Llama 3 8BHermes 2 Pro Llama 3 8B $0.14 · 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 · Hermes 2 Pro Llama 3 8B 8,192 tokens
- Widest inputsSame inputsGLM-4.5-Air: Text · Hermes 2 Pro Llama 3 8B: Text · Codestral 25.08: Text
- Self-hostingGLM-4.5-Air and Hermes 2 Pro Llama 3 8BPublishes downloadable weights (Llama 3 Community License)
| Measure | Weight | GLM-4.5-Air | Hermes 2 Pro Llama 3 8B | Codestral 25.08 |
|---|---|---|---|---|
| Price | 50% | 65 | 87 | 64 |
| Inputs & features | 30% | 35 | 25 | 35 |
| Context window | 20% | 25 | 0 | 24 |
| Overall | 100% | 48/100 | 51/100 | 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) | Hermes 2 Pro Llama 3 8BNous Research | Codestral 25.08Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.14 (best) | $0.30 |
| Output | $1.10 | $0.14 (best) | $0.90 |
| Cached input | $0.03 | — | $0.03 |
| Blended (3:1) | $0.425 | $0.14 (best) | $0.45 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 2 providers | Official Mistral API |
| Limits | |||
| Context window | 131,072 tokens (best) | 8,192 tokens | 128,000 tokens |
| Max output | 98,304 tokens (best) | 8,192 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | OpenLlama 3 Community License | Proprietary |
| API model ID | glm-4.5-air | — | codestral-2508 |
| API providers | 19 (best) | 2 | 11 |
| Released | Jul 28, 2025 | Apr 30, 2024 | 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
- Hermes 2 Pro Llama 3 8B$1.68
- Codestral 25.08$4.80
Which should you choose?
Which is better: GLM-4.5-Air, Hermes 2 Pro Llama 3 8B or Codestral 25.08?
Hermes 2 Pro Llama 3 8B is the better all-round choice, scoring 51/100 against GLM-4.5-Air (48) and Codestral 25.08 (47). It leads on price. 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, Hermes 2 Pro Llama 3 8B or Codestral 25.08?
Hermes 2 Pro Llama 3 8B is cheaper at $0.14 input / $0.14 output per million tokens (median across 2 API providers). 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 $0.14 per million tokens for Hermes 2 Pro Llama 3 8B versus $0.425 for GLM-4.5-Air (3× as much) and $0.45 for Codestral 25.08 (3.2× 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, Hermes 2 Pro Llama 3 8B 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, Hermes 2 Pro Llama 3 8B 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 8,192 for Hermes 2 Pro Llama 3 8B. Maximum output per response: GLM-4.5-Air up to 98,304, Hermes 2 Pro Llama 3 8B up to 8,192, Codestral 25.08 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Air accepts text; Hermes 2 Pro Llama 3 8B accepts text; Codestral 25.08 accepts text. They handle the same number of input types.
Are any of these open source?
GLM-4.5-Air and Hermes 2 Pro Llama 3 8B publishes its weights (Llama 3 Community License) 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; Hermes 2 Pro Llama 3 8B came out Apr 30, 2024. 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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