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Comparison · 3 models · Updated Oct 4, 2026

Claude Sonnet 3.7 vs DeepSeek-R1 vs GPT-4.1

Too close to call on our weighted score (GPT-4.1 53, DeepSeek-R1 51, Claude Sonnet 3.7 50). The right pick depends on what you value most.

  1. Anthropic

    Claude Sonnet 3.7

    Released Feb 19, 2025

    50/100
    • ECI141.2
    • Price$3.00 / $15.00
    • Context200K
    Full specs Remove Claude Sonnet 3.7

  2. DeepSeek

    DeepSeek-R1

    Released Jan 20, 2025

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

  3. OpenAI

    GPT-4.1

    Released Apr 14, 2025

    53/100
    • ECI136.8
    • Price$2.00 / $8.00
    • Context1.05M
    Full specs Remove GPT-4.1
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (GPT-4.1 53/100, DeepSeek-R1 51/100, Claude Sonnet 3.7 50/100), so choose by what matters most for your work: Claude Sonnet 3.7 for raw capability, DeepSeek-R1 on price and GPT-4.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityClaude Sonnet 3.7Capabilities Index (ECI): Claude Sonnet 3.7 141.2 · DeepSeek-R1 139.0 · GPT-4.1 136.8
  • Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · GPT-4.1 $3.50 · Claude Sonnet 3.7 $6.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-4.1GPT-4.1 1,047,576 · Claude Sonnet 3.7 200,000 · DeepSeek-R1 128,000 tokens
  • Widest inputsClaude Sonnet 3.7 and GPT-4.1Claude Sonnet 3.7: Text, Images, PDFs · DeepSeek-R1: Text · GPT-4.1: Text, Images, PDFs
  • Self-hostingDeepSeek-R1Publishes downloadable weights
How the score is built
MeasureWeightClaude Sonnet 3.7DeepSeek-R1GPT-4.1
CapabilityCapabilities Index (ECI)50%676461
Price25%134724
Inputs & features15%703570
Context window10%322461
Overall100%50/10051/10053/100
02 — Side by side

Every spec in one table

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

Claude Sonnet 3.7 vs DeepSeek-R1 vs GPT-4.1 specifications side by side
SpecificationClaude Sonnet 3.7AnthropicDeepSeek-R1DeepSeekGPT-4.1OpenAI
Capability
Capabilities Index (ECI)141.2 (best)139.0136.8
ECI rank#96 of 148 (best)#104 of 148#111 of 148
GPQA DiamondGraduate-level science questions79.7% (best)71.7%66.9%
FrontierMath Tiers 1–3Research-level mathematics——6.0%
OTIS Mock AIME 2024–2025Competition mathematics57.8% (best)53.3%38.3%
SWE-bench VerifiedFixing real GitHub issues61.0% (best)—48.5%
SimpleQA VerifiedShort factual questions——31.1%
Price per million tokens
Input$3.00$0.70 (best)$2.00
Output$15.00$2.60 (best)$8.00
Cached input——$0.50
Blended (3:1)$6.00$1.18 (best)$3.50
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 3 providersMedian of 11 providersOfficial OpenAI API
Limits
Context window200,000 tokens128,000 tokens1,047,576 tokens (best)
Max output64,000 tokens (best)32,768 tokens32,768 tokens
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsYesNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsProprietaryOpenProprietary
API model ID——gpt-4.1
API providers31225 (best)
ReleasedFeb 19, 2025Jan 20, 2025Apr 14, 2025
Knowledge cutoffOct 31, 2024Jul 2024Apr 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.

  • Claude Sonnet 3.7$60.00
  • DeepSeek-R1$12.20
  • GPT-4.1$36.00
04 — Questions

Which should you choose?

Which is better: Claude Sonnet 3.7, DeepSeek-R1 or GPT-4.1?

It is close. Our weighted score puts them within 2 points (GPT-4.1 53/100, DeepSeek-R1 51/100, Claude Sonnet 3.7 50/100), so choose by what matters most for your work: Claude Sonnet 3.7 for raw capability, DeepSeek-R1 on price and GPT-4.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Claude Sonnet 3.7, DeepSeek-R1 or GPT-4.1?

DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). GPT-4.1 costs $2.00 input / $8.00 output per million tokens (official OpenAI API price); Claude Sonnet 3.7 costs $3.00 input / $15.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $1.18 per million tokens for DeepSeek-R1 versus $3.50 for GPT-4.1 (3× as much) and $6.00 for Claude Sonnet 3.7 (5.1× as much).

Which scores higher on benchmarks?

Claude Sonnet 3.7 scores higher on the Capabilities Index (ECI): Claude Sonnet 3.7 141.2 (#96 of 148), DeepSeek-R1 139.0 (#104 of 148) and GPT-4.1 136.8 (#111 of 148). The confidence ranges of the top two overlap (138.7–142.9 vs 136.2–140.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Claude Sonnet 3.7 79.7%, DeepSeek-R1 71.7%, GPT-4.1 66.9%; OTIS Mock AIME 2024–2025 — Claude Sonnet 3.7 57.8%, DeepSeek-R1 53.3%, GPT-4.1 38.3%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-R1 yet, so there is no like-for-like coding score. On overall capability, Claude Sonnet 3.7 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?

GPT-4.1 has the largest context window at 1,047,576 tokens, against 200,000 for Claude Sonnet 3.7 and 128,000 for DeepSeek-R1. Maximum output per response: Claude Sonnet 3.7 up to 64,000, DeepSeek-R1 up to 32,768, GPT-4.1 up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Claude Sonnet 3.7 accepts text, images and PDFs; DeepSeek-R1 accepts text; GPT-4.1 accepts text, images and PDFs. Claude Sonnet 3.7 handles the widest range of inputs.

Are any of these open source?

DeepSeek-R1 publishes its weights and can be self-hosted; Claude Sonnet 3.7 and GPT-4.1 is proprietary.

Which is newer?

GPT-4.1 is the newest, released Apr 14, 2025. Claude Sonnet 3.7 came out Feb 19, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: Claude Sonnet 3.7 Oct 31, 2024, DeepSeek-R1 Jul 2024, GPT-4.1 Apr 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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