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Comparison · 3 models · Updated Oct 4, 2026

o3-mini vs Claude Haiku 4.5 vs DeepSeek-R1

Claude Haiku 4.5 comes out ahead, 58 to 52 and 51 on our weighted score, though DeepSeek-R1 is 41% cheaper per token.

  1. OpenAI

    o3-mini

    Released Jan 31, 2025Deprecated

    52/100
    • ECI140.3
    • Price$1.10 / $4.40
    • Context200K
    Full specs Remove o3-mini
  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. DeepSeek

    DeepSeek-R1

    Released Jan 20, 2025

    51/100
    • ECI139.0
    • Price$0.70 / $2.60
    • Context128K
    Full specs Remove DeepSeek-R1
01 — Verdict

Claude Haiku 4.5 is our pick

Claude Haiku 4.5 is the better all-round choice, scoring 58/100 against o3-mini (52) and DeepSeek-R1 (51). It leads on capability and inputs & features. DeepSeek-R1 wins on price. 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 · o3-mini 140.3 · DeepSeek-R1 139.0
  • Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · o3-mini $1.93 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
  • Longest contexto3-mini and Claude Haiku 4.5o3-mini 200,000 · Claude Haiku 4.5 200,000 · DeepSeek-R1 128,000 tokens
  • Widest inputsClaude Haiku 4.5o3-mini: Text · Claude Haiku 4.5: Text, Images, PDFs · DeepSeek-R1: Text
  • Self-hostingDeepSeek-R1Publishes downloadable weights
How the score is built
MeasureWeighto3-miniClaude Haiku 4.5DeepSeek-R1
CapabilityCapabilities Index (ECI)50%666964
Price25%363647
Inputs & features15%458035
Context window10%323224
Overall100%52/10058/10051/100
02 — Side by side

Every spec in one table

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

o3-mini vs Claude Haiku 4.5 vs DeepSeek-R1 specifications side by side
Specificationo3-miniOpenAIClaude Haiku 4.5AnthropicDeepSeek-R1DeepSeek
Capability
Capabilities Index (ECI)140.3142.4 (best)139.0
ECI rank#98 of 148#90 of 148 (best)#104 of 148
GPQA DiamondGraduate-level science questions77.0% (best)71.2%71.7%
FrontierMath Tiers 1–3Research-level mathematics18.6%——
OTIS Mock AIME 2024–2025Competition mathematics76.9% (best)66.7%53.3%
SimpleQA VerifiedShort factual questions15.3% (best)13.2%—
Price per million tokens
Input$1.10$1.00$0.70 (best)
Output$4.40$5.00$2.60 (best)
Cached input$0.55$0.10 (best)—
Blended (3:1)$1.93$2.00$1.18 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial OpenAI APIOfficial Anthropic APIMedian of 11 providers
Limits
Context window200,000 tokens (best)200,000 tokens (best)128,000 tokens
Max output100,000 tokens (best)64,000 tokens32,768 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningYeslow · medium · highYesYes
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsProprietaryProprietaryOpen
API model IDo3-miniclaude-haiku-4-5—
API providers1534 (best)12
ReleasedJan 31, 2025Oct 15, 2025Jan 20, 2025
Knowledge cutoffMay 2024Feb 28, 2025Jul 2024
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.

  • o3-mini$19.80
  • Claude Haiku 4.5$20.00
  • DeepSeek-R1$12.20
04 — Questions

Which should you choose?

Which is better: o3-mini, Claude Haiku 4.5 or DeepSeek-R1?

Claude Haiku 4.5 is the better all-round choice, scoring 58/100 against o3-mini (52) and DeepSeek-R1 (51). It leads on capability and inputs & features. DeepSeek-R1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, o3-mini, Claude Haiku 4.5 or DeepSeek-R1?

DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). o3-mini costs $1.10 input / $4.40 output per million tokens (official OpenAI 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 $1.93 for o3-mini (1.6× 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), o3-mini 140.3 (#98 of 148) and DeepSeek-R1 139.0 (#104 of 148). The confidence ranges of the top two overlap (139.5–144.3 vs 137.4–141.9), so treat the gap as small. On individual benchmarks: GPQA Diamond — o3-mini 77.0%, DeepSeek-R1 71.7%, Claude Haiku 4.5 71.2%; OTIS Mock AIME 2024–2025 — o3-mini 76.9%, Claude Haiku 4.5 66.7%, DeepSeek-R1 53.3%.

Which is better for coding?

There are no published SWE-bench Verified results for o3-mini, Claude Haiku 4.5 and DeepSeek-R1 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?

o3-mini and Claude Haiku 4.5 have the largest context windows (200,000 and 200,000 tokens), against 128,000 for DeepSeek-R1. Maximum output per response: o3-mini up to 100,000, Claude Haiku 4.5 up to 64,000, DeepSeek-R1 up to 32,768 tokens.

Which can read images, PDFs, audio or video?

o3-mini accepts text; Claude Haiku 4.5 accepts text, images and PDFs; DeepSeek-R1 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; o3-mini and Claude Haiku 4.5 is proprietary.

Which is newer?

Claude Haiku 4.5 is the newest, released Oct 15, 2025. o3-mini came out Jan 31, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: o3-mini May 2024, Claude Haiku 4.5 Feb 28, 2025, DeepSeek-R1 Jul 2024.

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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