DeepSeek-R1-Distill-Qwen-32B vs o1 vs Claude Opus 4
Too close to call on our weighted score (o1 65, Claude Opus 4 64, DeepSeek-R1-Distill-Qwen-32B 47). The right pick depends on what you value most.
DeepSeek
DeepSeek-R1-Distill-Qwen-32B
47/100- ECI137.4
- Price—
- Context131K
OpenAI
o1
65/100- ECI141.9
- Price$15.00 / $60.00
- Context200K
Anthropic
Claude Opus 4
64/100- ECI142.7
- Price$15.00 / $75.00
- Context200K
Too close to call
It is close. Our weighted score puts them within 1 points (o1 65/100, Claude Opus 4 64/100, DeepSeek-R1-Distill-Qwen-32B 47/100), so choose by what matters most for your work: Claude Opus 4 for raw capability and o1 on price. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityClaude Opus 4Capabilities Index (ECI): Claude Opus 4 142.7 · o1 141.9 · DeepSeek-R1-Distill-Qwen-32B 137.4
- Lowest priceo1o1 $26.25 · Claude Opus 4 $30.00 per 1M tokens (3:1 blend) · DeepSeek-R1-Distill-Qwen-32B unpriced
- Longest contexto1 and Claude Opus 4o1 200,000 · Claude Opus 4 200,000 · DeepSeek-R1-Distill-Qwen-32B 131,072 tokens
- Widest inputso1 and Claude Opus 4DeepSeek-R1-Distill-Qwen-32B: Text · o1: Text, Images, PDFs · Claude Opus 4: Text, Images, PDFs
- Self-hostingDeepSeek-R1-Distill-Qwen-32BPublishes downloadable weights
| Measure | Weight | DeepSeek-R1-Distill-Qwen-32B | o1 | Claude Opus 4 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 62 | 68 | 69 |
| Inputs & features | 20% | 10 | 80 | 70 |
| Context window | 13% | 24 | 32 | 32 |
| Overall | 100% | 47/100 | 65/100 | 64/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 137.4 | 141.9 | 142.7 (best) |
| ECI rank | #110 of 148 | #92 of 148 | #87 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 64.1% | 76.8% (best) | 76.3% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 14.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 55.6% | 73.3% (best) | 64.4% |
| SWE-bench VerifiedFixing real GitHub issues | — | — | 70.7% |
| SimpleQA VerifiedShort factual questions | — | 41.1% | — |
| Price per million tokens | |||
| Input | — | $15.00 | $15.00 |
| Output | — | $60.00 (best) | $75.00 |
| Cached input | — | $7.50 | — |
| Blended (3:1) | — | $26.25 (best) | $30.00 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official OpenAI API | Median of 5 providers |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens (best) | 200,000 tokens (best) |
| Max output | 32,768 tokens | 100,000 tokens (best) | 32,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · medium · high | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | — | o1 | — |
| API providers | — | 9 (best) | 5 |
| Released | Jan 20, 2025 | Dec 5, 2024 | May 22, 2025 |
| Knowledge cutoff | — | Sep 2023 | Mar 31, 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-Distill-Qwen-32B—
o1$270.00
Claude Opus 4$300.00
Which should you choose?
Which is better: DeepSeek-R1-Distill-Qwen-32B, o1 or Claude Opus 4?
It is close. Our weighted score puts them within 1 points (o1 65/100, Claude Opus 4 64/100, DeepSeek-R1-Distill-Qwen-32B 47/100), so choose by what matters most for your work: Claude Opus 4 for raw capability and o1 on price. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, DeepSeek-R1-Distill-Qwen-32B, o1 or Claude Opus 4?
o1 is cheaper at $15.00 input / $60.00 output per million tokens (official OpenAI API price). Claude Opus 4 costs $15.00 input / $75.00 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $26.25 per million tokens for o1 versus $30.00 for Claude Opus 4 (1.1× as much). DeepSeek-R1-Distill-Qwen-32B has no published per-token price.
Which scores higher on benchmarks?
Claude Opus 4 scores higher on the Capabilities Index (ECI): Claude Opus 4 142.7 (#87 of 148), o1 141.9 (#92 of 148) and DeepSeek-R1-Distill-Qwen-32B 137.4 (#110 of 148). The confidence ranges of the top two overlap (140.2–144.2 vs 139.7–143.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — o1 76.8%, Claude Opus 4 76.3%, DeepSeek-R1-Distill-Qwen-32B 64.1%; OTIS Mock AIME 2024–2025 — o1 73.3%, Claude Opus 4 64.4%, DeepSeek-R1-Distill-Qwen-32B 55.6%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1-Distill-Qwen-32B and o1 yet, so there is no like-for-like coding score. On overall capability, Claude Opus 4 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?
o1 and Claude Opus 4 have the largest context windows (200,000 and 200,000 tokens), against 131,072 for DeepSeek-R1-Distill-Qwen-32B. Maximum output per response: DeepSeek-R1-Distill-Qwen-32B up to 32,768, o1 up to 100,000, Claude Opus 4 up to 32,000 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1-Distill-Qwen-32B accepts text; o1 accepts text, images and PDFs; Claude Opus 4 accepts text, images and PDFs. o1 handles the widest range of inputs.
Are any of these open source?
DeepSeek-R1-Distill-Qwen-32B publishes its weights and can be self-hosted; o1 and Claude Opus 4 is proprietary.
Which is newer?
Claude Opus 4 is the newest, released May 22, 2025. DeepSeek-R1-Distill-Qwen-32B came out Jan 20, 2025; o1 came out Dec 5, 2024. Knowledge cutoff: o1 Sep 2023, Claude Opus 4 Mar 31, 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.