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Comparison · 3 models · Updated Oct 4, 2026

DeepSeek-R1-Distill-Qwen-32B vs o3-pro vs Claude Opus 4

o3-pro comes out ahead, 68 to 64 and 47 on our weighted score, though Claude Opus 4 is 14% cheaper per token.

  1. DeepSeek

    DeepSeek-R1-Distill-Qwen-32B

    Released Jan 20, 2025

    47/100
    • ECI137.4
    • Price—
    • Context131K
  2. Our pick

    OpenAI

    o3-pro

    Released Jun 10, 2025

    68/100
    • ECI147.4
    • Price$20.00 / $80.00
    • Context200K
  3. Anthropic

    Claude Opus 4

    Released May 22, 2025

    64/100
    • ECI142.7
    • Price$15.00 / $75.00
    • Context200K
01 — Verdict

o3-pro is our pick

o3-pro is the better all-round choice, scoring 68/100 against Claude Opus 4 (64) and DeepSeek-R1-Distill-Qwen-32B (47). It leads on capability. The score weighs capability 67%, inputs & features 20%, context window 13%.

  • Capabilityo3-proCapabilities Index (ECI): o3-pro 147.4 · Claude Opus 4 142.7 · DeepSeek-R1-Distill-Qwen-32B 137.4
  • Lowest priceClaude Opus 4Claude Opus 4 $30.00 · o3-pro $35.00 per 1M tokens (3:1 blend) · DeepSeek-R1-Distill-Qwen-32B unpriced
  • Longest contexto3-pro and Claude Opus 4o3-pro 200,000 · Claude Opus 4 200,000 · DeepSeek-R1-Distill-Qwen-32B 131,072 tokens
  • Widest inputsClaude Opus 4DeepSeek-R1-Distill-Qwen-32B: Text · o3-pro: Text, Images · Claude Opus 4: Text, Images, PDFs
  • Self-hostingDeepSeek-R1-Distill-Qwen-32BPublishes downloadable weights
How the score is built
MeasureWeightDeepSeek-R1-Distill-Qwen-32Bo3-proClaude Opus 4
CapabilityCapabilities Index (ECI)67%627569
Inputs & features20%107070
Context window13%243232
Overall100%47/10068/10064/100

Left out because at least one model lacks the data: price. 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-Distill-Qwen-32B vs o3-pro vs Claude Opus 4 specifications side by side
SpecificationDeepSeek-R1-Distill-Qwen-32BDeepSeeko3-proOpenAIClaude Opus 4Anthropic
Capability
Capabilities Index (ECI)137.4147.4 (best)142.7
ECI rank#110 of 148#60 of 148 (best)#87 of 148
GPQA DiamondGraduate-level science questions64.1%—76.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics55.6%—64.4% (best)
SWE-bench VerifiedFixing real GitHub issues——70.7%
Price per million tokens
Input—$20.00$15.00 (best)
Output—$80.00$75.00 (best)
Cached input———
Blended (3:1)—$35.00$30.00 (best)
Long-context rate—Same rateSame rate
Price source—Official OpenAI APIMedian of 5 providers
Limits
Context window131,072 tokens200,000 tokens (best)200,000 tokens (best)
Max output32,768 tokens100,000 tokens (best)32,000 tokens
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningYesYeslow · medium · highYes
Tool callingNoYesYes
Structured outputNoYesNo
Availability
WeightsOpenProprietaryProprietary
API model ID—o3-pro—
API providers—6 (best)5
ReleasedJan 20, 2025Jun 10, 2025May 22, 2025
Knowledge cutoff—May 2024Mar 31, 2025
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-Distill-Qwen-32B—
  • o3-pro$360.00
  • Claude Opus 4$300.00
04 — Questions

Which should you choose?

Which is better: DeepSeek-R1-Distill-Qwen-32B, o3-pro or Claude Opus 4?

o3-pro is the better all-round choice, scoring 68/100 against Claude Opus 4 (64) and DeepSeek-R1-Distill-Qwen-32B (47). It leads on capability. The score weighs capability 67%, inputs & features 20%, context window 13%.

Which is cheaper, DeepSeek-R1-Distill-Qwen-32B, o3-pro or Claude Opus 4?

Claude Opus 4 is cheaper at $15.00 input / $75.00 output per million tokens (median across 5 API providers). o3-pro costs $20.00 input / $80.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $30.00 per million tokens for Claude Opus 4 versus $35.00 for o3-pro (1.2× as much). DeepSeek-R1-Distill-Qwen-32B has no published per-token price.

Which scores higher on benchmarks?

o3-pro scores higher on the Capabilities Index (ECI): o3-pro 147.4 (#60 of 148), Claude Opus 4 142.7 (#87 of 148) and DeepSeek-R1-Distill-Qwen-32B 137.4 (#110 of 148). Their confidence ranges do not overlap (145.8–149.7 vs 140.2–144.2), so the gap is a real one.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-R1-Distill-Qwen-32B and o3-pro yet, so there is no like-for-like coding score. On overall capability, o3-pro 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?

o3-pro 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, o3-pro 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; o3-pro accepts text and images; Claude Opus 4 accepts text, images and PDFs. Claude Opus 4 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; o3-pro and Claude Opus 4 is proprietary.

Which is newer?

o3-pro is the newest, released Jun 10, 2025. Claude Opus 4 came out May 22, 2025; DeepSeek-R1-Distill-Qwen-32B came out Jan 20, 2025. Knowledge cutoff: o3-pro May 2024, 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.