Qwen3-Coder 480B-A35B Instruct vs Sonar Reasoning Pro

It is close. Our weighted score puts them within 1 points (Qwen3-Coder 480B-A35B Instruct 28/100, Sonar Reasoning Pro 27/100), so choose by what matters most for your work: Qwen3-Coder 480B-A35B Instruct on price and Qwen3-Coder 480B-A35B Instruct for long inputs. 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.

Qwen3-Coder 480B-A35B Instruct is cheaper at $1.50 input / $7.50 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 $3.00 per million tokens for Qwen3-Coder 480B-A35B Instruct versus $3.50 for Sonar Reasoning Pro (1.2× as much).

There is no independent benchmark that covers both models yet. Qwen3-Coder 480B-A35B Instruct has not been scored yet and Sonar Reasoning Pro has not been scored yet.

There are no published SWE-bench Verified results for Qwen3-Coder 480B-A35B 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.

Qwen3-Coder 480B-A35B Instruct has the largest context window at 262,144 tokens, against 128,000 for Sonar Reasoning Pro. Maximum output per response: Qwen3-Coder 480B-A35B Instruct up to 65,536, Sonar Reasoning Pro up to 4,096 tokens.

Qwen3-Coder 480B-A35B Instruct accepts text; Sonar Reasoning Pro accepts text and images. Sonar Reasoning Pro handles the widest range of inputs.

Qwen3-Coder 480B-A35B Instruct publishes its weights and can be self-hosted; Sonar Reasoning Pro is proprietary.

Qwen3-Coder 480B-A35B Instruct is the newest, released Apr 2025. Sonar Reasoning Pro came out Jan 1, 2024. Knowledge cutoff: Qwen3-Coder 480B-A35B Instruct Apr 2025, Sonar Reasoning Pro Sep 1, 2025.

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.