DeepSeek-R1 vs DeepSeek-R1-Distill-Qwen-32B vs Qwen3 235B-A22B
Too close to call on our weighted score (Qwen3 235B-A22B 53, DeepSeek-R1 53, DeepSeek-R1-Distill-Qwen-32B 47). The right pick depends on what you value most.
DeepSeekDeepSeek-R1
53/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
- DeepSeek
DeepSeek-R1-Distill-Qwen-32B
47/100- ECI137.4
- Price—
- Context131K
Alibaba (Qwen)Qwen3 235B-A22B
53/100- ECI139.4
- Price$0.70 / $2.80
- Context131K
Too close to call
It is close. Our weighted score puts them within a point (Qwen3 235B-A22B 53/100, DeepSeek-R1 53/100, DeepSeek-R1-Distill-Qwen-32B 47/100), so choose by what matters most for your work: Qwen3 235B-A22B for raw capability and DeepSeek-R1 on price. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityQwen3 235B-A22BCapabilities Index (ECI): Qwen3 235B-A22B 139.4 · DeepSeek-R1 139.0 · DeepSeek-R1-Distill-Qwen-32B 137.4
- Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · Qwen3 235B-A22B $1.23 per 1M tokens (3:1 blend) · DeepSeek-R1-Distill-Qwen-32B unpriced
- Longest contextDeepSeek-R1-Distill-Qwen-32B and Qwen3 235B-A22BDeepSeek-R1-Distill-Qwen-32B 131,072 · Qwen3 235B-A22B 131,072 · DeepSeek-R1 128,000 tokens
- Widest inputsSame inputsDeepSeek-R1: Text · DeepSeek-R1-Distill-Qwen-32B: Text · Qwen3 235B-A22B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek-R1 | DeepSeek-R1-Distill-Qwen-32B | Qwen3 235B-A22B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 64 | 62 | 65 |
| Inputs & features | 20% | 35 | 10 | 35 |
| Context window | 13% | 24 | 24 | 24 |
| Overall | 100% | 53/100 | 47/100 | 53/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-R1DeepSeek | DeepSeek-R1-Distill-Qwen-32BDeepSeek | Qwen3 235B-A22BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 139.0 | 137.4 | 139.4 (best) |
| ECI rank | #104 of 148 | #110 of 148 | #103 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 71.7% (best) | 64.1% | 70.7% |
| OTIS Mock AIME 2024–2025Competition mathematics | 53.3% | 55.6% (best) | — |
| Price per million tokens | |||
| Input | $0.70 | — | $0.70 |
| Output | $2.60 (best) | — | $2.80 |
| Cached input | — | — | — |
| Blended (3:1) | $1.18 (best) | — | $1.23 |
| Long-context rate | Same rate | — | Same rate |
| Price source | Median of 11 providers | — | Official Alibaba API |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Max output | 32,768 tokens (best) | 32,768 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | — | qwen3-235b-a22b |
| API providers | 12 (best) | — | 7 |
| Released | Jan 20, 2025 | Jan 20, 2025 | Apr 28, 2025 |
| Knowledge cutoff | Jul 2024 | — | Apr 2025 |
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$12.20
- DeepSeek-R1-Distill-Qwen-32B—
- Qwen3 235B-A22B$12.60
Which should you choose?
Which is better: DeepSeek-R1, DeepSeek-R1-Distill-Qwen-32B or Qwen3 235B-A22B?
It is close. Our weighted score puts them within a point (Qwen3 235B-A22B 53/100, DeepSeek-R1 53/100, DeepSeek-R1-Distill-Qwen-32B 47/100), so choose by what matters most for your work: Qwen3 235B-A22B for raw capability and DeepSeek-R1 on price. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, DeepSeek-R1, DeepSeek-R1-Distill-Qwen-32B or Qwen3 235B-A22B?
DeepSeek-R1 is cheaper at $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 $1.18 per million tokens for DeepSeek-R1 versus $1.23 for Qwen3 235B-A22B (1× as much). DeepSeek-R1-Distill-Qwen-32B has no published per-token price.
Which scores higher on benchmarks?
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 DeepSeek-R1-Distill-Qwen-32B 137.4 (#110 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%, DeepSeek-R1-Distill-Qwen-32B 64.1%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1, DeepSeek-R1-Distill-Qwen-32B 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. Note that DeepSeek-R1-Distill-Qwen-32B does not support tool calling, which most coding agents need.
Which has the bigger context window?
DeepSeek-R1-Distill-Qwen-32B 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, DeepSeek-R1-Distill-Qwen-32B up to 32,768, Qwen3 235B-A22B up to 16,384 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1 accepts text; DeepSeek-R1-Distill-Qwen-32B accepts text; Qwen3 235B-A22B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Qwen3 235B-A22B is the newest, released Apr 28, 2025. DeepSeek-R1 came out Jan 20, 2025; DeepSeek-R1-Distill-Qwen-32B came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, Qwen3 235B-A22B Apr 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.
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