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Comparison · 3 models · Updated Oct 4, 2026

Claude Haiku 4.5 vs DeepSeek-R1 vs Qwen3 Max

Claude Haiku 4.5 comes out ahead, 58 to 51 and 50 on our weighted score, though DeepSeek-R1 is 41% cheaper per token.

  1. Our pick

    Anthropic

    Claude Haiku 4.5

    Released Oct 15, 2025

    58/100
    • ECI142.4
    • Price$1.00 / $5.00
    • Context200K
  2. DeepSeek

    DeepSeek-R1

    Released Jan 20, 2025

    51/100
    • ECI139.0
    • Price$0.70 / $2.60
    • Context128K
  3. Alibaba (Qwen)

    Qwen3 Max

    Released Sep 23, 2025

    50/100
    • ECI142.4
    • Price$1.20 / $6.00
    • Context262K
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 Max (50). It leads on inputs & features. DeepSeek-R1 wins on price. Qwen3 Max wins on 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 · Qwen3 Max 142.4 · DeepSeek-R1 139.0
  • Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · Claude Haiku 4.5 $2.00 · Qwen3 Max $2.40 per 1M tokens (3:1 blend)
  • Longest contextQwen3 MaxQwen3 Max 262,144 · Claude Haiku 4.5 200,000 · DeepSeek-R1 128,000 tokens
  • Widest inputsClaude Haiku 4.5Claude Haiku 4.5: Text, Images, PDFs · DeepSeek-R1: Text · Qwen3 Max: Text
  • Self-hostingDeepSeek-R1Publishes downloadable weights
How the score is built
MeasureWeightClaude Haiku 4.5DeepSeek-R1Qwen3 Max
CapabilityCapabilities Index (ECI)50%696468
Price25%364732
Inputs & features15%803525
Context window10%322437
Overall100%58/10051/10050/100
02 — Side by side

Every spec in one table

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

Claude Haiku 4.5 vs DeepSeek-R1 vs Qwen3 Max specifications side by side
SpecificationClaude Haiku 4.5AnthropicDeepSeek-R1DeepSeekQwen3 MaxAlibaba (Qwen)
Capability
Capabilities Index (ECI)142.4 (best)139.0142.4
ECI rank#90 of 148 (best)#104 of 148#91 of 148
GPQA DiamondGraduate-level science questions71.2%71.7%72.6% (best)
FrontierMath Tiers 1–3Research-level mathematics——19.0%
OTIS Mock AIME 2024–2025Competition mathematics66.7%53.3%73.3% (best)
SimpleQA VerifiedShort factual questions13.2%—48.8% (best)
Price per million tokens
Input$1.00$0.70 (best)$1.20
Output$5.00$2.60 (best)$6.00
Cached input$0.10——
Blended (3:1)$2.00$1.18 (best)$2.40
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Anthropic APIMedian of 11 providersOfficial Alibaba API
Limits
Context window200,000 tokens128,000 tokens262,144 tokens (best)
Max output64,000 tokens32,768 tokens65,536 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsYesNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsProprietaryOpenProprietary
API model IDclaude-haiku-4-5—qwen3-max
API providers34 (best)1216
ReleasedOct 15, 2025Jan 20, 2025Sep 23, 2025
Knowledge cutoffFeb 28, 2025Jul 2024Apr 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.

  • Claude Haiku 4.5$20.00
  • DeepSeek-R1$12.20
  • Qwen3 Max$24.00
04 — Questions

Which should you choose?

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

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

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

DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). Claude Haiku 4.5 costs $1.00 input / $5.00 output per million tokens (official Anthropic API price); Qwen3 Max costs $1.20 input / $6.00 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 $2.00 for Claude Haiku 4.5 (1.7× as much) and $2.40 for Qwen3 Max (2× 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), Qwen3 Max 142.4 (#91 of 148) and DeepSeek-R1 139.0 (#104 of 148). The confidence ranges of the top two overlap (139.5–144.3 vs 140.0–144.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3 Max 72.6%, DeepSeek-R1 71.7%, Claude Haiku 4.5 71.2%; OTIS Mock AIME 2024–2025 — Qwen3 Max 73.3%, Claude Haiku 4.5 66.7%, DeepSeek-R1 53.3%.

Which is better for coding?

There are no published SWE-bench Verified results for Claude Haiku 4.5, DeepSeek-R1 and Qwen3 Max 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?

Qwen3 Max has the largest context window at 262,144 tokens, against 200,000 for Claude Haiku 4.5 and 128,000 for DeepSeek-R1. Maximum output per response: Claude Haiku 4.5 up to 64,000, DeepSeek-R1 up to 32,768, Qwen3 Max up to 65,536 tokens.

Which can read images, PDFs, audio or video?

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

Are any of these open source?

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

Which is newer?

Claude Haiku 4.5 is the newest, released Oct 15, 2025. Qwen3 Max came out Sep 23, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: Claude Haiku 4.5 Feb 28, 2025, DeepSeek-R1 Jul 2024, Qwen3 Max 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.