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Comparison · 3 models · Updated Oct 4, 2026

DeepSeek-R1 vs Claude Haiku 4.5 vs Qwen3 32B

Claude Haiku 4.5 comes out ahead, 58 to 51 and 51 on our weighted score, though DeepSeek-R1 is 41% cheaper per token.

  1. DeepSeek

    DeepSeek-R1

    Released Jan 20, 2025

    51/100
    • ECI139.0
    • Price$0.70 / $2.60
    • Context128K
    Full specs Remove DeepSeek-R1
  2. Our pick

    Anthropic

    Claude Haiku 4.5

    Released Oct 15, 2025

    58/100
    • ECI142.4
    • Price$1.00 / $5.00
    • Context200K
    Full specs Remove Claude Haiku 4.5

  3. Alibaba (Qwen)

    Qwen3 32B

    Released Apr 29, 2025

    51/100
    • ECI138.5
    • Price$0.70 / $2.80
    • Context131K
    Full specs Remove Qwen3 32B
01 — Verdict

Claude Haiku 4.5 is our pick

Claude Haiku 4.5 is the better all-round choice, scoring 58/100 against DeepSeek-R1 (51) and Qwen3 32B (51). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityClaude Haiku 4.5Capabilities Index (ECI): Claude Haiku 4.5 142.4 · DeepSeek-R1 139.0 · Qwen3 32B 138.5
  • Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · Qwen3 32B $1.23 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
  • Longest contextClaude Haiku 4.5Claude Haiku 4.5 200,000 · Qwen3 32B 131,072 · DeepSeek-R1 128,000 tokens
  • Widest inputsClaude Haiku 4.5DeepSeek-R1: Text · Claude Haiku 4.5: Text, Images, PDFs · Qwen3 32B: Text
  • Self-hostingDeepSeek-R1 and Qwen3 32BPublishes downloadable weights
How the score is built
MeasureWeightDeepSeek-R1Claude Haiku 4.5Qwen3 32B
CapabilityCapabilities Index (ECI)50%646964
Price25%473646
Inputs & features15%358035
Context window10%243224
Overall100%51/10058/10051/100
02 — Side by side

Every spec in one table

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

DeepSeek-R1 vs Claude Haiku 4.5 vs Qwen3 32B specifications side by side
SpecificationDeepSeek-R1DeepSeekClaude Haiku 4.5AnthropicQwen3 32BAlibaba (Qwen)
Capability
Capabilities Index (ECI)139.0142.4 (best)138.5
ECI rank#104 of 148#90 of 148 (best)#106 of 148
GPQA DiamondGraduate-level science questions71.7% (best)71.2%65.7%
OTIS Mock AIME 2024–2025Competition mathematics53.3%66.7%66.9% (best)
SimpleQA VerifiedShort factual questions—13.2%—
Price per million tokens
Input$0.70 (best)$1.00$0.70 (best)
Output$2.60 (best)$5.00$2.80
Cached input—$0.10—
Blended (3:1)$1.18 (best)$2.00$1.23
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 11 providersOfficial Anthropic APIOfficial Alibaba API
Limits
Context window128,000 tokens200,000 tokens (best)131,072 tokens
Max output32,768 tokens64,000 tokens (best)16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenProprietaryOpen
API model ID—claude-haiku-4-5qwen3-32b
API providers1234 (best)14
ReleasedJan 20, 2025Oct 15, 2025Apr 29, 2025
Knowledge cutoffJul 2024Feb 28, 2025Apr 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$12.20
  • Claude Haiku 4.5$20.00
  • Qwen3 32B$12.60
04 — Questions

Which should you choose?

Which is better: DeepSeek-R1, Claude Haiku 4.5 or Qwen3 32B?

Claude Haiku 4.5 is the better all-round choice, scoring 58/100 against DeepSeek-R1 (51) and Qwen3 32B (51). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek-R1, Claude Haiku 4.5 or Qwen3 32B?

DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). Qwen3 32B costs $0.70 input / $2.80 output per million tokens (official Alibaba API price); Claude Haiku 4.5 costs $1.00 input / $5.00 output per million tokens (official Anthropic 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 32B (1× as much) and $2.00 for Claude Haiku 4.5 (1.7× as much).

Which scores higher on benchmarks?

Claude Haiku 4.5 scores higher on the Capabilities Index (ECI): Claude Haiku 4.5 142.4 (#90 of 148), DeepSeek-R1 139.0 (#104 of 148) and Qwen3 32B 138.5 (#106 of 148). The confidence ranges of the top two overlap (139.5–144.3 vs 136.2–140.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-R1 71.7%, Claude Haiku 4.5 71.2%, Qwen3 32B 65.7%; OTIS Mock AIME 2024–2025 — Qwen3 32B 66.9%, Claude Haiku 4.5 66.7%, DeepSeek-R1 53.3%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-R1, Claude Haiku 4.5 and Qwen3 32B yet, so there is no like-for-like coding score. On overall capability, Claude Haiku 4.5 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

Claude Haiku 4.5 has the largest context window at 200,000 tokens, against 131,072 for Qwen3 32B and 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, Claude Haiku 4.5 up to 64,000, Qwen3 32B up to 16,384 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-R1 accepts text; Claude Haiku 4.5 accepts text, images and PDFs; Qwen3 32B accepts text. Claude Haiku 4.5 handles the widest range of inputs.

Are any of these open source?

DeepSeek-R1 and Qwen3 32B publishes its weights and can be self-hosted; Claude Haiku 4.5 is proprietary.

Which is newer?

Claude Haiku 4.5 is the newest, released Oct 15, 2025. Qwen3 32B came out Apr 29, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, Claude Haiku 4.5 Feb 28, 2025, Qwen3 32B 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.

05 — Keep comparing

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