Qwen3-Coder 480B-A35B Instruct vs Command A vs Pixtral Large (25.02)
Pixtral Large (25.02) comes out ahead, 33 to 28 and 24 on our weighted score.
Alibaba (Qwen)Qwen3-Coder 480B-A35B Instruct
28/100- ECI—
- Price$1.50 / $7.50
- Context262K
CohereCommand A
24/100- ECI—
- Price$2.50 / $10.00
- Context256K
- Our pick
Mistral AIPixtral Large (25.02)
33/100- ECI—
- Price$2.00 / $6.00
- Context128K
Pixtral Large (25.02) is our pick
Pixtral Large (25.02) is the better all-round choice, scoring 33/100 against Qwen3-Coder 480B-A35B Instruct (28) and Command A (24). It leads on 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 priceQwen3-Coder 480B-A35B Instruct and Pixtral Large (25.02)Qwen3-Coder 480B-A35B Instruct $3.00 · Pixtral Large (25.02) $3.00 · Command A $4.38 per 1M tokens (3:1 blend)
- Longest contextQwen3-Coder 480B-A35B InstructQwen3-Coder 480B-A35B Instruct 262,144 · Command A 256,000 · Pixtral Large (25.02) 128,000 tokens
- Widest inputsPixtral Large (25.02)Qwen3-Coder 480B-A35B Instruct: Text · Command A: Text · Pixtral Large (25.02): Text, Images
- Self-hostingQwen3-Coder 480B-A35B Instruct and Command APublishes downloadable weights
| Measure | Weight | Qwen3-Coder 480B-A35B Instruct | Command A | Pixtral Large (25.02) |
|---|---|---|---|---|
| Price | 50% | 27 | 19 | 27 |
| Inputs & features | 30% | 25 | 25 | 50 |
| Context window | 20% | 37 | 36 | 24 |
| Overall | 100% | 28/100 | 24/100 | 33/100 |
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 | Qwen3-Coder 480B-A35B InstructAlibaba (Qwen) | Command ACohere | Pixtral Large (25.02)Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.50 (best) | $2.50 | $2.00 |
| Output | $7.50 | $10.00 | $6.00 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $3.00 (best) | $4.38 | $3.00 (best) |
| Long-context rate | Over 32K: $2.70 / $13.50 | Same rate | Same rate |
| Price source | Official Alibaba API | Official Cohere API | Median of 3 providers |
| Limits | |||
| Context window | 262,144 tokens (best) | 256,000 tokens | 128,000 tokens |
| Max output | 65,536 tokens (best) | 8,000 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | qwen3-coder-480b-a35b-instruct | command-a-03-2025 | — |
| API providers | 7 (best) | 3 | 3 |
| Released | Apr 2025 | Mar 13, 2025 | Apr 8, 2025 |
| Knowledge cutoff | Apr 2025 | Jun 1, 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3-Coder 480B-A35B Instruct$30.00
- Command A$45.00
- Pixtral Large (25.02)$32.00
Which should you choose?
Which is better: Qwen3-Coder 480B-A35B Instruct, Command A or Pixtral Large (25.02)?
Pixtral Large (25.02) is the better all-round choice, scoring 33/100 against Qwen3-Coder 480B-A35B Instruct (28) and Command A (24). It leads on 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, Qwen3-Coder 480B-A35B Instruct, Command A or Pixtral Large (25.02)?
Qwen3-Coder 480B-A35B Instruct is cheaper at $1.50 input / $7.50 output per million tokens (official Alibaba API price). Pixtral Large (25.02) costs $2.00 input / $6.00 output per million tokens (median across 3 API providers); Command A costs $2.50 input / $10.00 output per million tokens (official Cohere API price). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Qwen3-Coder 480B-A35B Instruct versus $3.00 for Pixtral Large (25.02) (1× as much) and $4.38 for Command A (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3-Coder 480B-A35B Instruct has not been scored yet, Command A has not been scored yet and Pixtral Large (25.02) has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3-Coder 480B-A35B Instruct, Command A and Pixtral Large (25.02) 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?
Qwen3-Coder 480B-A35B Instruct has the largest context window at 262,144 tokens, against 256,000 for Command A and 128,000 for Pixtral Large (25.02). Maximum output per response: Qwen3-Coder 480B-A35B Instruct up to 65,536, Command A up to 8,000, Pixtral Large (25.02) up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Qwen3-Coder 480B-A35B Instruct accepts text; Command A accepts text; Pixtral Large (25.02) accepts text and images. Pixtral Large (25.02) handles the widest range of inputs.
Are any of these open source?
Qwen3-Coder 480B-A35B Instruct and Command A publishes its weights and can be self-hosted; Pixtral Large (25.02) is proprietary.
Which is newer?
Pixtral Large (25.02) is the newest, released Apr 8, 2025. Qwen3-Coder 480B-A35B Instruct came out Apr 2025; Command A came out Mar 13, 2025. Knowledge cutoff: Qwen3-Coder 480B-A35B Instruct Apr 2025, Command A Jun 1, 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.
