Sonar Reasoning Pro vs Qwen2.5-VL 7B Instruct vs Qwen Max
Qwen2.5-VL 7B Instruct comes out ahead, 51 to 27 and 22 on our weighted score, and it is the cheaper option too.
PerplexitySonar Reasoning Pro
27/100- ECI—
- Price$2.00 / $8.00
- Context128K
- Our pick
Alibaba (Qwen)Qwen2.5-VL 7B Instruct
51/100- ECI—
- Price$0.35 / $1.05
- Context131K
- Alibaba (Qwen)
Qwen Max
22/100- ECI—
- Price$1.60 / $6.40
- Context33K
Qwen2.5-VL 7B Instruct is our pick
Qwen2.5-VL 7B Instruct is the better all-round choice, scoring 51/100 against Sonar Reasoning Pro (27) and Qwen Max (22). It leads on price and 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 priceQwen2.5-VL 7B InstructQwen2.5-VL 7B Instruct $0.525 · Qwen Max $2.80 · Sonar Reasoning Pro $3.50 per 1M tokens (3:1 blend)
- Longest contextQwen2.5-VL 7B InstructQwen2.5-VL 7B Instruct 131,072 · Sonar Reasoning Pro 128,000 · Qwen Max 32,768 tokens
- Widest inputsSonar Reasoning Pro and Qwen2.5-VL 7B InstructSonar Reasoning Pro: Text, Images · Qwen2.5-VL 7B Instruct: Text, Images · Qwen Max: Text
- Self-hostingQwen2.5-VL 7B InstructPublishes downloadable weights
| Measure | Weight | Sonar Reasoning Pro | Qwen2.5-VL 7B Instruct | Qwen Max |
|---|---|---|---|---|
| Price | 50% | 24 | 63 | 29 |
| Inputs & features | 30% | 35 | 50 | 25 |
| Context window | 20% | 24 | 24 | 0 |
| Overall | 100% | 27/100 | 51/100 | 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 | Qwen2.5-VL 7B InstructAlibaba (Qwen) | Qwen MaxAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.00 | $0.35 (best) | $1.60 |
| Output | $8.00 | $1.05 (best) | $6.40 |
| Cached input | — | — | — |
| Blended (3:1) | $3.50 | $0.525 (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 | 128,000 tokens | 131,072 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 | Open | Proprietary |
| API model ID | sonar-reasoning-pro | qwen2-5-vl-7b-instruct | qwen-max |
| API providers | 4 | 1 | 6 (best) |
| Released | Jan 1, 2024 | Sep 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 Reasoning Pro$36.00
- Qwen2.5-VL 7B Instruct$5.60
- Qwen Max$28.80
Which should you choose?
Which is better: Sonar Reasoning Pro, Qwen2.5-VL 7B Instruct or Qwen Max?
Qwen2.5-VL 7B Instruct is the better all-round choice, scoring 51/100 against Sonar Reasoning Pro (27) and Qwen Max (22). It leads on price and 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, Qwen2.5-VL 7B Instruct or Qwen Max?
Qwen2.5-VL 7B Instruct is cheaper at $0.35 input / $1.05 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 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 $0.525 per million tokens for Qwen2.5-VL 7B Instruct versus $2.80 for Qwen Max (5.3× as much) and $3.50 for Sonar Reasoning Pro (6.7× 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, Qwen2.5-VL 7B Instruct 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, Qwen2.5-VL 7B Instruct 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?
Qwen2.5-VL 7B Instruct has the largest context window at 131,072 tokens, against 128,000 for Sonar Reasoning Pro and 32,768 for Qwen Max. Maximum output per response: Sonar Reasoning Pro up to 4,096, Qwen2.5-VL 7B Instruct 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; Qwen2.5-VL 7B Instruct accepts text and images; Qwen Max accepts text. Sonar Reasoning Pro handles the widest range of inputs.
Are any of these open source?
Qwen2.5-VL 7B Instruct publishes its weights and can be self-hosted; Sonar Reasoning Pro and Qwen Max is proprietary.
Which is newer?
Qwen2.5-VL 7B Instruct is the newest, released Sep 2024. Qwen Max came out Apr 3, 2024; Sonar Reasoning Pro came out Jan 1, 2024. Knowledge cutoff: Sonar Reasoning Pro Sep 1, 2025, Qwen2.5-VL 7B Instruct 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.
