Qwen Max vs Pixtral Large (25.02) vs Sonar Reasoning Pro
Pixtral Large (25.02) comes out ahead, 33 to 27 and 22 on our weighted score, though Qwen Max is 7% cheaper per token.
Alibaba (Qwen)Qwen Max
22/100- ECI—
- Price$1.60 / $6.40
- Context33K
- Our pick
Mistral AIPixtral Large (25.02)
33/100- ECI—
- Price$2.00 / $6.00
- Context128K
PerplexitySonar Reasoning Pro
27/100- ECI—
- Price$2.00 / $8.00
- Context128K
Pixtral Large (25.02) is our pick
Pixtral Large (25.02) is the better all-round choice, scoring 33/100 against Sonar Reasoning Pro (27) and Qwen Max (22). 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 priceQwen MaxQwen Max $2.80 · Pixtral Large (25.02) $3.00 · Sonar Reasoning Pro $3.50 per 1M tokens (3:1 blend)
- Longest contextPixtral Large (25.02) and Sonar Reasoning ProPixtral Large (25.02) 128,000 · Sonar Reasoning Pro 128,000 · Qwen Max 32,768 tokens
- Widest inputsPixtral Large (25.02) and Sonar Reasoning ProQwen Max: Text · Pixtral Large (25.02): Text, Images · Sonar Reasoning Pro: Text, Images
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Qwen Max | Pixtral Large (25.02) | Sonar Reasoning Pro |
|---|---|---|---|---|
| Price | 50% | 29 | 27 | 24 |
| Inputs & features | 30% | 25 | 50 | 35 |
| Context window | 20% | 0 | 24 | 24 |
| Overall | 100% | 22/100 | 33/100 | 27/100 |
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 | Qwen MaxAlibaba (Qwen) | Pixtral Large (25.02)Mistral AI | Sonar Reasoning ProPerplexity |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.60 (best) | $2.00 | $2.00 |
| Output | $6.40 | $6.00 (best) | $8.00 |
| Cached input | — | — | — |
| Blended (3:1) | $2.80 (best) | $3.00 | $3.50 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 3 providers | Official Perplexity API |
| Limits | |||
| Context window | 32,768 tokens | 128,000 tokens (best) | 128,000 tokens (best) |
| Max output | 8,192 tokens (best) | 8,192 tokens (best) | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yesminimal · low · medium · high |
| Tool calling | Yes | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | qwen-max | — | sonar-reasoning-pro |
| API providers | 6 (best) | 3 | 4 |
| Released | Apr 3, 2024 | Apr 8, 2025 | Jan 1, 2024 |
| Knowledge cutoff | Apr 2024 | — | Sep 1, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen Max$28.80
- Pixtral Large (25.02)$32.00
- Sonar Reasoning Pro$36.00
Which should you choose?
Which is better: Qwen Max, Pixtral Large (25.02) or Sonar Reasoning Pro?
Pixtral Large (25.02) is the better all-round choice, scoring 33/100 against Sonar Reasoning Pro (27) and Qwen Max (22). 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, Qwen Max, Pixtral Large (25.02) or Sonar Reasoning Pro?
Qwen Max is cheaper at $1.60 input / $6.40 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); Sonar Reasoning Pro costs $2.00 input / $8.00 output per million tokens (official Perplexity API price). At a typical mix of three input tokens to one output token, that is $2.80 per million tokens for Qwen Max versus $3.00 for Pixtral Large (25.02) (1.1× as much) and $3.50 for Sonar Reasoning Pro (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen Max has not been scored yet, Pixtral Large (25.02) has not been scored yet and Sonar Reasoning Pro has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen Max, Pixtral Large (25.02) and Sonar Reasoning Pro yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Sonar Reasoning Pro does not support tool calling, which most coding agents need.
Which has the bigger context window?
Pixtral Large (25.02) and Sonar Reasoning Pro have the largest context windows (128,000 and 128,000 tokens), against 32,768 for Qwen Max. Maximum output per response: Qwen Max up to 8,192, Pixtral Large (25.02) up to 8,192, Sonar Reasoning Pro up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Qwen Max accepts text; Pixtral Large (25.02) accepts text and images; Sonar Reasoning Pro accepts text and images. Pixtral Large (25.02) handles the widest range of inputs.
Are any of these open source?
No. Qwen Max, Pixtral Large (25.02) and Sonar Reasoning Pro are proprietary and only available through APIs and apps.
Which is newer?
Pixtral Large (25.02) is the newest, released Apr 8, 2025. Qwen Max came out Apr 3, 2024; Sonar Reasoning Pro came out Jan 1, 2024. Knowledge cutoff: Qwen Max Apr 2024, Sonar Reasoning Pro Sep 1, 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 Oct 4, 2026.
