Qwen Max vs Qwen2.5-VL 7B Instruct vs Sonar Reasoning Pro
Qwen2.5-VL 7B Instruct comes out ahead, 51 to 27 and 22 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen Max
22/100- ECI—
- Price$1.60 / $6.40
- Context33K
- Our pickAlibaba (Qwen)
Qwen2.5-VL 7B Instruct
51/100- ECI—
- Price$0.35 / $1.05
- Context131K
PerplexitySonar Reasoning Pro
27/100- ECI—
- Price$2.00 / $8.00
- Context128K
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 inputsQwen2.5-VL 7B Instruct and Sonar Reasoning ProQwen Max: Text · Qwen2.5-VL 7B Instruct: Text, Images · Sonar Reasoning Pro: Text, Images
- Self-hostingQwen2.5-VL 7B InstructPublishes downloadable weights
| Measure | Weight | Qwen Max | Qwen2.5-VL 7B Instruct | Sonar Reasoning Pro |
|---|---|---|---|---|
| Price | 50% | 29 | 63 | 24 |
| Inputs & features | 30% | 25 | 50 | 35 |
| Context window | 20% | 0 | 24 | 24 |
| Overall | 100% | 22/100 | 51/100 | 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) | Qwen2.5-VL 7B InstructAlibaba (Qwen) | Sonar Reasoning ProPerplexity |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.60 | $0.35 (best) | $2.00 |
| Output | $6.40 | $1.05 (best) | $8.00 |
| Cached input | — | — | — |
| Blended (3:1) | $2.80 | $0.525 (best) | $3.50 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Alibaba API | Official Perplexity API |
| Limits | |||
| Context window | 32,768 tokens | 131,072 tokens (best) | 128,000 tokens |
| 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 | Open | Proprietary |
| API model ID | qwen-max | qwen2-5-vl-7b-instruct | sonar-reasoning-pro |
| API providers | 6 (best) | 1 | 4 |
| Released | Apr 3, 2024 | Sep 2024 | Jan 1, 2024 |
| Knowledge cutoff | Apr 2024 | 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
- Qwen2.5-VL 7B Instruct$5.60
- Sonar Reasoning Pro$36.00
Which should you choose?
Which is better: Qwen Max, Qwen2.5-VL 7B Instruct or Sonar Reasoning Pro?
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, Qwen Max, Qwen2.5-VL 7B Instruct or Sonar Reasoning Pro?
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. Qwen Max has not been scored yet, Qwen2.5-VL 7B Instruct 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, Qwen2.5-VL 7B Instruct 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?
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: Qwen Max up to 8,192, Qwen2.5-VL 7B Instruct up to 8,192, Sonar Reasoning Pro up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Qwen Max accepts text; Qwen2.5-VL 7B Instruct accepts text and images; Sonar Reasoning Pro accepts text and images. Qwen2.5-VL 7B Instruct 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; Qwen Max and Sonar Reasoning Pro 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: Qwen Max Apr 2024, Qwen2.5-VL 7B Instruct 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.
