Sonar Pro vs Qwen Plus Character (Japanese) vs Qwen Max
Qwen Plus Character (Japanese) comes out ahead, 36 to 22 and 20 on our weighted score, and it is the cheaper option too.
PerplexitySonar Pro
20/100- ECI—
- Price$3.00 / $15.00
- Context200K
- Our pick
Alibaba (Qwen)Qwen Plus Character (Japanese)
36/100- ECI—
- Price$0.50 / $1.40
- Context8K
- Alibaba (Qwen)
Qwen Max
22/100- ECI—
- Price$1.60 / $6.40
- Context33K
Qwen Plus Character (Japanese) is our pick
Qwen Plus Character (Japanese) is the better all-round choice, scoring 36/100 against Qwen Max (22) and Sonar Pro (20). It leads on price. Sonar Pro wins on context window. 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 Plus Character (Japanese)Qwen Plus Character (Japanese) $0.725 · Qwen Max $2.80 · Sonar Pro $6.00 per 1M tokens (3:1 blend)
- Longest contextSonar ProSonar Pro 200,000 · Qwen Max 32,768 · Qwen Plus Character (Japanese) 8,192 tokens
- Widest inputsSonar ProSonar Pro: Text, Images · Qwen Plus Character (Japanese): Text · Qwen Max: Text
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Sonar Pro | Qwen Plus Character (Japanese) | Qwen Max |
|---|---|---|---|---|
| Price | 50% | 13 | 57 | 29 |
| Inputs & features | 30% | 25 | 25 | 25 |
| Context window | 20% | 32 | 0 | 0 |
| Overall | 100% | 20/100 | 36/100 | 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 ProPerplexity | Qwen Plus Character (Japanese)Alibaba (Qwen) | Qwen MaxAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $3.00 | $0.50 (best) | $1.60 |
| Output | $15.00 | $1.40 (best) | $6.40 |
| Cached input | — | — | — |
| Blended (3:1) | $6.00 | $0.725 (best) | $2.80 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Perplexity API | Official Alibaba API | Official Alibaba API |
| Limits | |||
| Context window | 200,000 tokens (best) | 8,192 tokens | 32,768 tokens |
| Max output | 8,192 tokens (best) | 512 tokens | 8,192 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | sonar-pro | qwen-plus-character-ja | qwen-max |
| API providers | 5 | 1 | 6 (best) |
| Released | Jan 1, 2024 | Jan 2024 | Apr 3, 2024 |
| Knowledge cutoff | Sep 1, 2025 | Apr 2024 | 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 Pro$60.00
- Qwen Plus Character (Japanese)$7.80
- Qwen Max$28.80
Which should you choose?
Which is better: Sonar Pro, Qwen Plus Character (Japanese) or Qwen Max?
Qwen Plus Character (Japanese) is the better all-round choice, scoring 36/100 against Qwen Max (22) and Sonar Pro (20). It leads on price. Sonar Pro wins on context window. 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 Pro, Qwen Plus Character (Japanese) or Qwen Max?
Qwen Plus Character (Japanese) is cheaper at $0.50 input / $1.40 output per million tokens (official Alibaba API price). Qwen Max costs $1.60 input / $6.40 output per million tokens (official Alibaba API price); Sonar Pro costs $3.00 input / $15.00 output per million tokens (official Perplexity API price). At a typical mix of three input tokens to one output token, that is $0.725 per million tokens for Qwen Plus Character (Japanese) versus $2.80 for Qwen Max (3.9× as much) and $6.00 for Sonar Pro (8.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Sonar Pro has not been scored yet, Qwen Plus Character (Japanese) 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 Pro, Qwen Plus Character (Japanese) 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 Pro does not support tool calling, which most coding agents need.
Which has the bigger context window?
Sonar Pro has the largest context window at 200,000 tokens, against 32,768 for Qwen Max and 8,192 for Qwen Plus Character (Japanese). Maximum output per response: Sonar Pro up to 8,192, Qwen Plus Character (Japanese) up to 512, Qwen Max up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Sonar Pro accepts text and images; Qwen Plus Character (Japanese) accepts text; Qwen Max accepts text. Sonar Pro handles the widest range of inputs.
Are any of these open source?
No. Sonar Pro, Qwen Plus Character (Japanese) 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 Pro came out Jan 1, 2024; Qwen Plus Character (Japanese) came out Jan 2024. Knowledge cutoff: Sonar Pro Sep 1, 2025, Qwen Plus Character (Japanese) Apr 2024, 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.
