Sonar Reasoning Pro vs Pixtral Large (25.02) vs Qwen Max
Pixtral Large (25.02) comes out ahead, 33 to 27 and 22 on our weighted score, though Qwen Max is 7% cheaper per token.
PerplexitySonar Reasoning Pro
27/100- ECI—
- Price$2.00 / $8.00
- Context128K
- Our pick
Mistral AIPixtral Large (25.02)
33/100- ECI—
- Price$2.00 / $6.00
- Context128K
Alibaba (Qwen)Qwen Max
22/100- ECI—
- Price$1.60 / $6.40
- Context33K
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 contextSonar Reasoning Pro and Pixtral Large (25.02)Sonar Reasoning Pro 128,000 · Pixtral Large (25.02) 128,000 · Qwen Max 32,768 tokens
- Widest inputsSonar Reasoning Pro and Pixtral Large (25.02)Sonar Reasoning Pro: Text, Images · Pixtral Large (25.02): Text, Images · Qwen Max: Text
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Sonar Reasoning Pro | Pixtral Large (25.02) | Qwen Max |
|---|---|---|---|---|
| Price | 50% | 24 | 27 | 29 |
| Inputs & features | 30% | 35 | 50 | 25 |
| Context window | 20% | 24 | 24 | 0 |
| Overall | 100% | 27/100 | 33/100 | 22/100 |
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 | Sonar Reasoning ProPerplexity | Pixtral Large (25.02)Mistral AI | Qwen MaxAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.00 | $2.00 | $1.60 (best) |
| Output | $8.00 | $6.00 (best) | $6.40 |
| Cached input | — | — | — |
| Blended (3:1) | $3.50 | $3.00 | $2.80 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Perplexity API | Median of 3 providers | Official Alibaba API |
| Limits | |||
| Context window | 128,000 tokens (best) | 128,000 tokens (best) | 32,768 tokens |
| Max output | 4,096 tokens | 8,192 tokens (best) | 8,192 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yesminimal · low · medium · high | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | sonar-reasoning-pro | — | qwen-max |
| API providers | 4 | 3 | 6 (best) |
| Released | Jan 1, 2024 | Apr 8, 2025 | Apr 3, 2024 |
| Knowledge cutoff | Sep 1, 2025 | — | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Sonar Reasoning Pro$36.00
- Pixtral Large (25.02)$32.00
- Qwen Max$28.80
Which should you choose?
Which is better: Sonar Reasoning Pro, Pixtral Large (25.02) or Qwen Max?
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, Sonar Reasoning Pro, Pixtral Large (25.02) or Qwen Max?
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. Sonar Reasoning Pro has not been scored yet, Pixtral Large (25.02) has not been scored yet and Qwen Max has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Sonar Reasoning Pro, Pixtral Large (25.02) and Qwen Max 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?
Sonar Reasoning Pro and Pixtral Large (25.02) have the largest context windows (128,000 and 128,000 tokens), against 32,768 for Qwen Max. Maximum output per response: Sonar Reasoning Pro up to 4,096, Pixtral Large (25.02) up to 8,192, Qwen Max up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Sonar Reasoning Pro accepts text and images; Pixtral Large (25.02) accepts text and images; Qwen Max accepts text. Sonar Reasoning Pro handles the widest range of inputs.
Are any of these open source?
No. Sonar Reasoning Pro, Pixtral Large (25.02) and Qwen Max 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: Sonar Reasoning Pro Sep 1, 2025, Qwen Max Apr 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.
