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Comparison · 2 models · Updated Nov 2, 2026

Claude Haiku 4.5 vs DeepSeek V4.1 Flash 1017

DeepSeek V4.1 Flash 1017 comes out ahead, 79 to 57 on our weighted score, and it is the cheaper option too.

  1. Anthropic

    Claude Haiku 4.5

    Released Oct 15, 2025

    57/100
    • ECI142.2
    • Price$1.00 / $5.00
    • Context200K
  2. Our pick

    DeepSeek

    DeepSeek V4.1 Flash 1017

    Released Oct 17, 2026New

    79/100
    • ECI158.8
    • Price$0.15 / $0.60
    • Context1M
  3. Add a model

    Make it a three-way comparison.

01 — Verdict

DeepSeek V4.1 Flash 1017 is our pick

DeepSeek V4.1 Flash 1017 is the better all-round choice, scoring 79/100 against Claude Haiku 4.5 (57). It leads on capability, price and context window. Claude Haiku 4.5 wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityDeepSeek V4.1 Flash 1017Capabilities Index (ECI): DeepSeek V4.1 Flash 1017 158.8 · Claude Haiku 4.5 142.2
  • Lowest priceDeepSeek V4.1 Flash 1017DeepSeek V4.1 Flash 1017 $0.263 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
  • Longest contextDeepSeek V4.1 Flash 1017DeepSeek V4.1 Flash 1017 1,000,000 · Claude Haiku 4.5 200,000 tokens
  • Widest inputsClaude Haiku 4.5Claude Haiku 4.5: Text, Images, PDFs · DeepSeek V4.1 Flash 1017: Text, Images
  • Self-hostingDeepSeek V4.1 Flash 1017Publishes downloadable weights (MIT)
How the score is built
MeasureWeightClaude Haiku 4.5DeepSeek V4.1 Flash 1017
CapabilityCapabilities Index (ECI)50%6787
Price25%3474
Inputs & features15%8070
Context window10%3260
Overall100%57/10079/100
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 V4.1 Flash 1017 specifications side by side
SpecificationClaude Haiku 4.5AnthropicDeepSeek V4.1 Flash 1017DeepSeek
Capability
Capabilities Index (ECI)142.2158.8 (best)
ECI rank#102 of 165#19 of 165 (best)
GPQA DiamondGraduate-level science questions71.2%93.2% (best)
FrontierMath Tiers 1–3Research-level mathematics—71.2%
OTIS Mock AIME 2024–2025Competition mathematics66.7%99.4% (best)
SimpleQA VerifiedShort factual questions13.2%42.5% (best)
Price per million tokens
Input$1.00$0.15 (best)
Output$5.00$0.60 (best)
Cached input$0.10$0.003 (best)
Blended (3:1)$2.00$0.263 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Anthropic APIOfficial DeepSeek API
Limits
Context window200,000 tokens1,000,000 tokens (best)
Max output64,000 tokens384,000 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsYesNo
AudioNoNo
VideoNoNo
ReasoningYesYeslow · high · max
Tool callingYesYes
Structured outputYesYes
Availability
WeightsProprietaryOpenMIT
API model IDclaude-haiku-4-5deepseek-flash
API providers48 (best)40
ReleasedOct 15, 2025Oct 17, 2026
Knowledge cutoffFeb 28, 2025May 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 V4.1 Flash 1017$2.70
04 — Questions

Which should you choose?

Which is better: Claude Haiku 4.5 or DeepSeek V4.1 Flash 1017?

DeepSeek V4.1 Flash 1017 is the better all-round choice, scoring 79/100 against Claude Haiku 4.5 (57). It leads on capability, price and context window. Claude Haiku 4.5 wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Claude Haiku 4.5 or DeepSeek V4.1 Flash 1017?

DeepSeek V4.1 Flash 1017 is cheaper at $0.15 input / $0.60 output per million tokens (official DeepSeek 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 $0.263 per million tokens for DeepSeek V4.1 Flash 1017 versus $2.00 for Claude Haiku 4.5 (7.6× as much).

Which scores higher on benchmarks?

DeepSeek V4.1 Flash 1017 scores higher on the Capabilities Index (ECI): DeepSeek V4.1 Flash 1017 158.8 (#19 of 165) and Claude Haiku 4.5 142.2 (#102 of 165). Their confidence ranges do not overlap (156.7–162.2 vs 139.4–143.9), so the gap is a real one. On individual benchmarks: GPQA Diamond — DeepSeek V4.1 Flash 1017 93.2%, Claude Haiku 4.5 71.2%; OTIS Mock AIME 2024–2025 — DeepSeek V4.1 Flash 1017 99.4%, Claude Haiku 4.5 66.7%; SimpleQA Verified — DeepSeek V4.1 Flash 1017 42.5%, Claude Haiku 4.5 13.2%.

Which is better for coding?

There are no published SWE-bench Verified results for Claude Haiku 4.5 and DeepSeek V4.1 Flash 1017 yet, so there is no like-for-like coding score. On overall capability, DeepSeek V4.1 Flash 1017 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

DeepSeek V4.1 Flash 1017 has the largest context window at 1,000,000 tokens, against 200,000 for Claude Haiku 4.5. Maximum output per response: Claude Haiku 4.5 up to 64,000, DeepSeek V4.1 Flash 1017 up to 384,000 tokens.

Which can read images, PDFs, audio or video?

Claude Haiku 4.5 accepts text, images and PDFs; DeepSeek V4.1 Flash 1017 accepts text and images. Claude Haiku 4.5 handles the widest range of inputs.

Are any of these open source?

DeepSeek V4.1 Flash 1017 publishes its weights (MIT) and can be self-hosted; Claude Haiku 4.5 is proprietary.

Which is newer?

DeepSeek V4.1 Flash 1017 is the newest, released Oct 17, 2026. Claude Haiku 4.5 came out Oct 15, 2025. Knowledge cutoff: Claude Haiku 4.5 Feb 28, 2025, DeepSeek V4.1 Flash 1017 May 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 Nov 2, 2026.