GLM-4.5-Air vs Seed-OSS-36B-Instruct vs Codestral 25.08
Seed-OSS-36B-Instruct comes out ahead, 40 to 31 and 31 on our weighted score.
Z.ai (Zhipu)GLM-4.5-Air
31/100- ECI—
- Price$0.20 / $1.10
- Context131K
- Our pick
ByteDance SeedSeed-OSS-36B-Instruct
40/100- ECI—
- Price—
- Context524K
Mistral AICodestral 25.08
31/100- ECI—
- Price$0.30 / $0.90
- Context128K
Seed-OSS-36B-Instruct is our pick
Seed-OSS-36B-Instruct is the better all-round choice, scoring 40/100 against GLM-4.5-Air (31) and Codestral 25.08 (31). It leads on 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-AirGLM-4.5-Air $0.425 · Codestral 25.08 $0.45 per 1M tokens (3:1 blend) · Seed-OSS-36B-Instruct unpriced
- Longest contextSeed-OSS-36B-InstructSeed-OSS-36B-Instruct 524,288 · GLM-4.5-Air 131,072 · Codestral 25.08 128,000 tokens
- Widest inputsSame inputsGLM-4.5-Air: Text · Seed-OSS-36B-Instruct: Text · Codestral 25.08: Text
- Self-hostingGLM-4.5-Air and Seed-OSS-36B-InstructPublishes downloadable weights (Apache 2.0)
| Measure | Weight | GLM-4.5-Air | Seed-OSS-36B-Instruct | Codestral 25.08 |
|---|---|---|---|---|
| Inputs & features | 60% | 35 | 35 | 35 |
| Context window | 40% | 25 | 49 | 24 |
| Overall | 100% | 31/100 | 40/100 | 31/100 |
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 | GLM-4.5-AirZ.ai (Zhipu) | Seed-OSS-36B-InstructByteDance Seed | Codestral 25.08Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| GPQA DiamondGraduate-level science questions | — | 71.5% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 67.5% | — |
| Price per million tokens | |||
| Input | $0.20 (best) | — | $0.30 |
| Output | $1.10 | — | $0.90 (best) |
| Cached input | $0.03 | — | $0.03 |
| Blended (3:1) | $0.425 (best) | — | $0.45 |
| Long-context rate | Same rate | — | Same rate |
| Price source | Official Z.AI API | — | Official Mistral API |
| Limits | |||
| Context window | 131,072 tokens | 524,288 tokens (best) | 128,000 tokens |
| Max output | 98,304 tokens | 524,288 tokens (best) | 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 | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Proprietary |
| API model ID | glm-4.5-air | — | codestral-2508 |
| API providers | 19 (best) | — | 11 |
| Released | Jul 28, 2025 | Aug 20, 2025 | Jul 30, 2025 |
| Knowledge cutoff | Apr 2025 | Jul 2024 | — |
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
- Seed-OSS-36B-Instruct—
- Codestral 25.08$4.80
Which should you choose?
Which is better: GLM-4.5-Air, Seed-OSS-36B-Instruct or Codestral 25.08?
Seed-OSS-36B-Instruct is the better all-round choice, scoring 40/100 against GLM-4.5-Air (31) and Codestral 25.08 (31). It leads on 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, GLM-4.5-Air, Seed-OSS-36B-Instruct or Codestral 25.08?
GLM-4.5-Air is cheaper at $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 $0.425 per million tokens for GLM-4.5-Air versus $0.45 for Codestral 25.08 (1.1× as much). Seed-OSS-36B-Instruct has no published per-token price.
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, Seed-OSS-36B-Instruct 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, Seed-OSS-36B-Instruct 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?
Seed-OSS-36B-Instruct has the largest context window at 524,288 tokens, against 131,072 for GLM-4.5-Air and 128,000 for Codestral 25.08. Maximum output per response: GLM-4.5-Air up to 98,304, Seed-OSS-36B-Instruct up to 524,288, Codestral 25.08 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Air accepts text; Seed-OSS-36B-Instruct 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 Seed-OSS-36B-Instruct publishes its weights (Apache 2.0) and can be self-hosted; Codestral 25.08 is proprietary.
Which is newer?
Seed-OSS-36B-Instruct is the newest, released Aug 20, 2025. Codestral 25.08 came out Jul 30, 2025; GLM-4.5-Air came out Jul 28, 2025. Knowledge cutoff: GLM-4.5-Air Apr 2025, Seed-OSS-36B-Instruct Jul 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 Nov 2, 2026.
Related comparisons
- GLM-4.5-Air vs Llama 3.3 Nemotron Super 49B v1.5NVIDIA
- GLM-4.5-Air vs Qwen3 Omni 30B A3B ThinkingAlibaba (Qwen)
- GLM-4.5-Air vs ERNIE 4.5 300B A47BBaidu
- Seed-OSS-36B-Instruct vs Claude Haiku 4.5Anthropic · ECI 142.2
- Seed-OSS-36B-Instruct vs GPT-5 NanoOpenAI · ECI 139.3
- Seed-OSS-36B-Instruct vs DeepSeek-R1DeepSeek · ECI 138.8
