ERNIE 4.5 300B A47B vs Codestral 25.08 vs GLM-4.5-Air
Too close to call on our weighted score (GLM-4.5-Air 48, Codestral 25.08 47, ERNIE 4.5 300B A47B 43). The right pick depends on what you value most.
Baidu
ERNIE 4.5 300B A47B
43/100- ECI—
- Price$0.28 / $1.10
- Context131K
Mistral AI
Codestral 25.08
47/100- ECI—
- Price$0.30 / $0.90
- Context128K
Z.ai (Zhipu)
GLM-4.5-Air
48/100- ECI—
- Price$0.20 / $1.10
- Context131K
Too close to call
It is close. Our weighted score puts them within a point (GLM-4.5-Air 48/100, Codestral 25.08 47/100, ERNIE 4.5 300B A47B 43/100), so choose by what matters most for your work: GLM-4.5-Air 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 priceGLM-4.5-AirGLM-4.5-Air $0.425 · Codestral 25.08 $0.45 · ERNIE 4.5 300B A47B $0.485 per 1M tokens (3:1 blend)
- Longest contextERNIE 4.5 300B A47B and GLM-4.5-AirERNIE 4.5 300B A47B 131,072 · GLM-4.5-Air 131,072 · Codestral 25.08 128,000 tokens
- Widest inputsSame inputsERNIE 4.5 300B A47B: Text · Codestral 25.08: Text · GLM-4.5-Air: Text
- Self-hostingERNIE 4.5 300B A47B and GLM-4.5-AirPublishes downloadable weights (Apache-2.0)
| Measure | Weight | ERNIE 4.5 300B A47B | Codestral 25.08 | GLM-4.5-Air |
|---|---|---|---|---|
| Price | 50% | 62 | 64 | 65 |
| Inputs & features | 30% | 25 | 35 | 35 |
| Context window | 20% | 25 | 24 | 25 |
| Overall | 100% | 43/100 | 47/100 | 48/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.28 | $0.30 | $0.20 (best) |
| Output | $1.10 | $0.90 (best) | $1.10 |
| Cached input | — | $0.03 | $0.03 |
| Blended (3:1) | $0.485 | $0.45 | $0.425 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Mistral API | Official Z.AI API |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 131,072 tokens (best) |
| Max output | 12,000 tokens | 8,192 tokens | 98,304 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Open |
| API model ID | — | codestral-2508 | glm-4.5-air |
| API providers | 1 | 11 | 19 (best) |
| Released | Jun 30, 2025 | Jul 30, 2025 | Jul 28, 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.
ERNIE 4.5 300B A47B$5.00
Codestral 25.08$4.80
GLM-4.5-Air$4.20
Which should you choose?
Which is better: ERNIE 4.5 300B A47B, Codestral 25.08 or GLM-4.5-Air?
It is close. Our weighted score puts them within a point (GLM-4.5-Air 48/100, Codestral 25.08 47/100, ERNIE 4.5 300B A47B 43/100), so choose by what matters most for your work: GLM-4.5-Air 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, ERNIE 4.5 300B A47B, Codestral 25.08 or GLM-4.5-Air?
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); ERNIE 4.5 300B A47B costs $0.28 input / $1.10 output per million tokens (median across 1 API provider). 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) and $0.485 for ERNIE 4.5 300B A47B (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. ERNIE 4.5 300B A47B has not been scored yet, Codestral 25.08 has not been scored yet and GLM-4.5-Air has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for ERNIE 4.5 300B A47B, Codestral 25.08 and GLM-4.5-Air 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?
ERNIE 4.5 300B A47B and GLM-4.5-Air have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Codestral 25.08. Maximum output per response: ERNIE 4.5 300B A47B up to 12,000, Codestral 25.08 up to 8,192, GLM-4.5-Air up to 98,304 tokens.
Which can read images, PDFs, audio or video?
ERNIE 4.5 300B A47B accepts text; Codestral 25.08 accepts text; GLM-4.5-Air accepts text. They handle the same number of input types.
Are any of these open source?
ERNIE 4.5 300B A47B and GLM-4.5-Air 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; ERNIE 4.5 300B A47B came out Jun 30, 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.