DeepSeek-R1 vs Qwen3 30B A3B vs Qwen3 235B-A22B

Qwen3 30B A3B is the better all-round choice, scoring 58/100 against Qwen3 235B-A22B (51) and DeepSeek-R1 (51). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Qwen3 30B A3B is cheaper at $0.114 input / $0.50 output per million tokens (median across 8 API providers). DeepSeek-R1 costs $0.70 input / $2.60 output per million tokens (median across 11 API providers); Qwen3 235B-A22B costs $0.70 input / $2.80 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.21 per million tokens for Qwen3 30B A3B versus $1.18 for DeepSeek-R1 (5.6× as much) and $1.23 for Qwen3 235B-A22B (5.8× as much).

Qwen3 235B-A22B scores higher on the Capabilities Index (ECI): Qwen3 235B-A22B 139.4 (#103 of 148), DeepSeek-R1 139.0 (#104 of 148) and Qwen3 30B A3B 136.2 (#112 of 148). The confidence ranges of the top two overlap (135.2–140.8 vs 136.2–140.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-R1 71.7%, Qwen3 235B-A22B 70.7%, Qwen3 30B A3B 61.7%.

There are no published SWE-bench Verified results for DeepSeek-R1, Qwen3 30B A3B and Qwen3 235B-A22B yet, so there is no like-for-like coding score. On overall capability, Qwen3 235B-A22B leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Qwen3 30B A3B and Qwen3 235B-A22B have the largest context windows (131,072 and 131,072 tokens), against 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, Qwen3 30B A3B up to 16,384, Qwen3 235B-A22B up to 16,384 tokens.

DeepSeek-R1 accepts text; Qwen3 30B A3B accepts text; Qwen3 235B-A22B accepts text. They handle the same number of input types.

Yes, all three publish their weights, so you can self-host them.

Qwen3 30B A3B is the newest, released Apr 28, 2025. Qwen3 235B-A22B came out Apr 28, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, Qwen3 235B-A22B Apr 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.