Baichuan M2 32B vs DeepSeek-R1 vs DeepSeek R1 0528 Qwen3 8B

It is close. Our weighted score puts them within a point (Baichuan M2 32B 58/100, DeepSeek R1 0528 Qwen3 8B 58/100, DeepSeek-R1 34/100), so choose by what matters most for your work: DeepSeek R1 0528 Qwen3 8B on price. 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.

DeepSeek R1 0528 Qwen3 8B is cheaper at $0.06 input / $0.09 output per million tokens (median across 1 API provider). Baichuan M2 32B costs $0.07 input / $0.07 output per million tokens (median across 1 API provider); DeepSeek-R1 costs $0.70 input / $4.88 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.068 per million tokens for DeepSeek R1 0528 Qwen3 8B versus $0.07 for Baichuan M2 32B (1× as much) and $1.75 for DeepSeek-R1 (26× as much).

There is no independent benchmark that covers all three models yet. Baichuan M2 32B has not been scored yet, DeepSeek-R1 has an ECI of 138.8 and DeepSeek R1 0528 Qwen3 8B has not been scored yet.

There are no published SWE-bench Verified results for Baichuan M2 32B, DeepSeek-R1 and DeepSeek R1 0528 Qwen3 8B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Baichuan M2 32B and DeepSeek R1 0528 Qwen3 8B does not support tool calling, which most coding agents need.

Baichuan M2 32B and DeepSeek R1 0528 Qwen3 8B have the largest context windows (131,072 and 131,072 tokens), against 128,000 for DeepSeek-R1. Maximum output per response: Baichuan M2 32B up to 131,072, DeepSeek-R1 up to 32,768, DeepSeek R1 0528 Qwen3 8B up to 32,000 tokens.

Baichuan M2 32B accepts text; DeepSeek-R1 accepts text; DeepSeek R1 0528 Qwen3 8B accepts text. They handle the same number of input types.

Yes, all three publish their weights (Apache-2.0 and MIT), so you can self-host them.

Baichuan M2 32B is the newest, released Aug 13, 2025. DeepSeek R1 0528 Qwen3 8B came out May 29, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024.

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 Nov 2, 2026.