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Comparison · 3 models · Updated Nov 2, 2026

DeepSeek-R1 vs Gemini 2.5 Flash vs GPT-4.1

Gemini 2.5 Flash comes out ahead, 66 to 52 and 48 on our weighted score, and it is the cheaper option too.

  1. DeepSeek

    DeepSeek-R1

    Released Jan 20, 2025

    48/100
    • ECI138.8
    • Price$0.70 / $4.88
    • Context128K
    Full specs Remove DeepSeek-R1
  2. Our pick

    Google

    Gemini 2.5 Flash

    Released Jun 17, 2025

    66/100
    • ECI140.6
    • Price$0.30 / $2.50
    • Context1.05M
    Full specs Remove Gemini 2.5 Flash

  3. OpenAI

    GPT-4.1

    Released Apr 14, 2025

    52/100
    • ECI136.7
    • Price$2.00 / $8.00
    • Context1.05M
    Full specs Remove GPT-4.1
01 — Verdict

Gemini 2.5 Flash is our pick

Gemini 2.5 Flash is the better all-round choice, scoring 66/100 against GPT-4.1 (52) and DeepSeek-R1 (48). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGemini 2.5 FlashCapabilities Index (ECI): Gemini 2.5 Flash 140.6 · DeepSeek-R1 138.8 · GPT-4.1 136.7
  • Lowest priceGemini 2.5 FlashGemini 2.5 Flash $0.85 · DeepSeek-R1 $1.75 · GPT-4.1 $3.50 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 Flash and GPT-4.1Gemini 2.5 Flash 1,048,576 · GPT-4.1 1,047,576 · DeepSeek-R1 128,000 tokens
  • Widest inputsGemini 2.5 FlashDeepSeek-R1: Text · Gemini 2.5 Flash: Text, Images, PDFs, Audio, Video · GPT-4.1: Text, Images, PDFs
  • Self-hostingDeepSeek-R1Publishes downloadable weights
How the score is built
MeasureWeightDeepSeek-R1Gemini 2.5 FlashGPT-4.1
CapabilityCapabilities Index (ECI)50%636560
Price25%375123
Inputs & features15%3510070
Context window10%246161
Overall100%48/10066/10052/100
02 — Side by side

Every spec in one table

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

DeepSeek-R1 vs Gemini 2.5 Flash vs GPT-4.1 specifications side by side
SpecificationDeepSeek-R1DeepSeekGemini 2.5 FlashGoogleGPT-4.1OpenAI
Capability
Capabilities Index (ECI)138.8140.6 (best)136.7
ECI rank#119 of 165#110 of 165 (best)#125 of 165
GPQA DiamondGraduate-level science questions71.7% (best)—66.9%
FrontierMath Tiers 1–3Research-level mathematics——6.0%
OTIS Mock AIME 2024–2025Competition mathematics53.3% (best)—38.3%
SWE-bench VerifiedFixing real GitHub issues——48.5%
SimpleQA VerifiedShort factual questions——31.1%
Price per million tokens
Input$0.70$0.30 (best)$2.00
Output$4.88$2.50 (best)$8.00
Cached input—$0.03 (best)$0.50
Blended (3:1)$1.75$0.85 (best)$3.50
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 11 providersOfficial Google APIOfficial OpenAI API
Limits
Context window128,000 tokens1,048,576 tokens (best)1,047,576 tokens
Max output32,768 tokens65,536 tokens (best)32,768 tokens
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoYesYes
AudioNoYesNo
VideoNoYesNo
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputNoYesYes
Availability
WeightsOpenProprietaryProprietary
API model ID—gemini-2.5-flashgpt-4.1
API providers1232 (best)31
ReleasedJan 20, 2025Jun 17, 2025Apr 14, 2025
Knowledge cutoffJul 2024Jan 2025Apr 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.

  • DeepSeek-R1$16.76
  • Gemini 2.5 Flash$8.00
  • GPT-4.1$36.00
04 — Questions

Which should you choose?

Which is better: DeepSeek-R1, Gemini 2.5 Flash or GPT-4.1?

Gemini 2.5 Flash is the better all-round choice, scoring 66/100 against GPT-4.1 (52) and DeepSeek-R1 (48). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek-R1, Gemini 2.5 Flash or GPT-4.1?

Gemini 2.5 Flash is cheaper at $0.30 input / $2.50 output per million tokens (official Google API price). DeepSeek-R1 costs $0.70 input / $4.88 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). At a typical mix of three input tokens to one output token, that is $0.85 per million tokens for Gemini 2.5 Flash versus $1.75 for DeepSeek-R1 (2.1× as much) and $3.50 for GPT-4.1 (4.1× as much).

Which scores higher on benchmarks?

Gemini 2.5 Flash scores higher on the Capabilities Index (ECI): Gemini 2.5 Flash 140.6 (#110 of 165), DeepSeek-R1 138.8 (#119 of 165) and GPT-4.1 136.7 (#125 of 165). The confidence ranges of the top two overlap (138.4–142.1 vs 136.5–140.2), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-R1 and Gemini 2.5 Flash yet, so there is no like-for-like coding score. On overall capability, Gemini 2.5 Flash 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?

Gemini 2.5 Flash and GPT-4.1 have the largest context windows (1,048,576 and 1,047,576 tokens), against 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, Gemini 2.5 Flash up to 65,536, GPT-4.1 up to 32,768 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-R1 accepts text; Gemini 2.5 Flash accepts text, images, PDFs, audio and video; GPT-4.1 accepts text, images and PDFs. Gemini 2.5 Flash handles the widest range of inputs.

Are any of these open source?

DeepSeek-R1 publishes its weights and can be self-hosted; Gemini 2.5 Flash and GPT-4.1 is proprietary.

Which is newer?

Gemini 2.5 Flash is the newest, released Jun 17, 2025. GPT-4.1 came out Apr 14, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, Gemini 2.5 Flash Jan 2025, 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 Nov 2, 2026.

05 — Keep comparing

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