Sonar vs Qwen Max
Sonar comes out ahead, 30 to 22 on our weighted score, and it is the cheaper option too.
Sonar is our pick
Sonar is the better all-round choice, scoring 30/100 against Qwen Max (22). It leads on price and context window. Qwen Max wins 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 priceSonarSonar $1.00 · Qwen Max $2.80 per 1M tokens (3:1 blend)
- Longest contextSonarSonar 128,000 · Qwen Max 32,768 tokens
- Widest inputsSame inputsSonar: Text · Qwen Max: Text
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | Sonar | Qwen Max |
|---|---|---|---|
| Price | 50% | 50 | 29 |
| Inputs & features | 30% | 0 | 25 |
| Context window | 20% | 24 | 0 |
| Overall | 100% | 30/100 | 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 |  SonarPerplexity |  Qwen MaxAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $1.00 (best) | $1.60 |
| Output | $1.00 (best) | $6.40 |
| Cached input | — | — |
| Blended (3:1) | $1.00 (best) | $2.80 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Perplexity API | Official Alibaba API |
| Limits | ||
| Context window | 128,000 tokens (best) | 32,768 tokens |
| Max output | 4,096 tokens | 8,192 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | No | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | sonar | qwen-max |
| API providers | 6 | 6 |
| Released | Jan 1, 2024 | 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$12.00
- Qwen Max$28.80
Which should you choose?
Which is better: Sonar or Qwen Max?
Sonar is the better all-round choice, scoring 30/100 against Qwen Max (22). It leads on price and context window. Qwen Max wins 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 or Qwen Max?
Sonar is cheaper at $1.00 input / $1.00 output per million tokens (official Perplexity API price). Qwen Max costs $1.60 input / $6.40 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $1.00 per million tokens for Sonar versus $2.80 for Qwen Max (2.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Sonar 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 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 does not support tool calling, which most coding agents need.
Which has the bigger context window?
Sonar has the largest context window at 128,000 tokens, against 32,768 for Qwen Max. Maximum output per response: Sonar up to 4,096, Qwen Max up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Sonar accepts text; Qwen Max accepts text. They handle the same number of input types.
Are any of these open source?
No. Sonar and Qwen Max are proprietary and only available through APIs and apps.
Which is newer?
Qwen Max is the newest, released Apr 3, 2024. Sonar came out Jan 1, 2024. Knowledge cutoff: Sonar 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.
