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Comparison · 3 models · Updated Nov 2, 2026

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

Too close to call on our weighted score (DeepSeek R1 0528 Qwen3 8B 58, Baichuan M2 32B 58, DeepSeek R1 0528 41). The right pick depends on what you value most.

  1. DeepSeek

    DeepSeek R1 0528 Qwen3 8B

    Released May 29, 2025

    58/100
    • ECI—
    • Price$0.06 / $0.09
    • Context131K
    Full specs Remove DeepSeek R1 0528 Qwen3 8B

  2. DeepSeek

    DeepSeek R1 0528

    Released May 28, 2025

    41/100
    • ECI141.2
    • Price$0.512 / $2.19
    • Context164K
    Full specs Remove DeepSeek R1 0528

  3. Baichuan

    Baichuan M2 32B

    Released Aug 13, 2025

    58/100
    • ECI—
    • Price$0.07 / $0.07
    • Context131K
    Full specs Remove Baichuan M2 32B
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (DeepSeek R1 0528 Qwen3 8B 58/100, Baichuan M2 32B 58/100, DeepSeek R1 0528 41/100), so choose by what matters most for your work: DeepSeek R1 0528 Qwen3 8B on price and DeepSeek R1 0528 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.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceDeepSeek R1 0528 Qwen3 8BDeepSeek R1 0528 Qwen3 8B $0.068 · Baichuan M2 32B $0.07 · DeepSeek R1 0528 $0.932 per 1M tokens (3:1 blend)
  • Longest contextDeepSeek R1 0528DeepSeek R1 0528 163,840 · DeepSeek R1 0528 Qwen3 8B 131,072 · Baichuan M2 32B 131,072 tokens
  • Widest inputsSame inputsDeepSeek R1 0528 Qwen3 8B: Text · DeepSeek R1 0528: Text · Baichuan M2 32B: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightDeepSeek R1 0528 Qwen3 8BDeepSeek R1 0528Baichuan M2 32B
Price50%10049100
Inputs & features30%103510
Context window20%252825
Overall100%58/10041/10058/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

DeepSeek R1 0528 Qwen3 8B vs DeepSeek R1 0528 vs Baichuan M2 32B specifications side by side
SpecificationDeepSeek R1 0528 Qwen3 8BDeepSeekDeepSeek R1 0528DeepSeekBaichuan M2 32BBaichuan
Capability
Capabilities Index (ECI)—141.2—
ECI rank—#108 of 165—
GPQA DiamondGraduate-level science questions9.3%76.3% (best)—
OTIS Mock AIME 2024–2025Competition mathematics43.9%66.4% (best)—
Price per million tokens
Input$0.06 (best)$0.512$0.07
Output$0.09$2.19$0.07 (best)
Cached input———
Blended (3:1)$0.068 (best)$0.932$0.07
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 1 providersMedian of 16 providersMedian of 1 providers
Limits
Context window131,072 tokens163,840 tokens (best)131,072 tokens
Max output32,000 tokens32,768 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingNoYesNo
Structured outputNoNoNo
Availability
WeightsOpenMITOpenMITOpenApache-2.0
API model ID———
API providers116 (best)1
ReleasedMay 29, 2025May 28, 2025Aug 13, 2025
Knowledge cutoff———
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • DeepSeek R1 0528 Qwen3 8B$0.78
  • DeepSeek R1 0528$9.50
  • Baichuan M2 32B$0.84
04 — Questions

Which should you choose?

Which is better: DeepSeek R1 0528 Qwen3 8B, DeepSeek R1 0528 or Baichuan M2 32B?

It is close. Our weighted score puts them within a point (DeepSeek R1 0528 Qwen3 8B 58/100, Baichuan M2 32B 58/100, DeepSeek R1 0528 41/100), so choose by what matters most for your work: DeepSeek R1 0528 Qwen3 8B on price and DeepSeek R1 0528 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.

Which is cheaper, DeepSeek R1 0528 Qwen3 8B, DeepSeek R1 0528 or Baichuan M2 32B?

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 0528 costs $0.512 input / $2.19 output per million tokens (median across 16 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 $0.932 for DeepSeek R1 0528 (14× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. DeepSeek R1 0528 Qwen3 8B has not been scored yet, DeepSeek R1 0528 has an ECI of 141.2 and Baichuan M2 32B has not been scored yet.

Which is better for coding?

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

Which has the bigger context window?

DeepSeek R1 0528 has the largest context window at 163,840 tokens, against 131,072 for DeepSeek R1 0528 Qwen3 8B and 131,072 for Baichuan M2 32B. Maximum output per response: DeepSeek R1 0528 Qwen3 8B up to 32,000, DeepSeek R1 0528 up to 32,768, Baichuan M2 32B up to 131,072 tokens.

Which can read images, PDFs, audio or video?

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

Are any of these open source?

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

Which is newer?

Baichuan M2 32B is the newest, released Aug 13, 2025. DeepSeek R1 0528 Qwen3 8B came out May 29, 2025; DeepSeek R1 0528 came out May 28, 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 Nov 2, 2026.

05 — Keep comparing

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