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Comparison · 3 models · Updated Oct 4, 2026

Gemini 2.0 Flash vs DeepSeek-R1 vs Claude Sonnet 3.5 v2

Gemini 2.0 Flash comes out ahead, 65 to 54 and 53 on our weighted score.

  1. Our pick

    Google

    Gemini 2.0 Flash

    Released Dec 11, 2024

    65/100
    • ECI134.7
    • Price—
    • Context1.05M
    Full specs Remove Gemini 2.0 Flash

  2. DeepSeek

    DeepSeek-R1

    Released Jan 20, 2025

    53/100
    • ECI139.0
    • Price$0.70 / $2.60
    • Context128K
    Full specs Remove DeepSeek-R1

  3. Anthropic

    Claude Sonnet 3.5 v2

    Released Oct 22, 2024

    54/100
    • ECI133.5
    • Price$3.00 / $15.00
    • Context200K
    Full specs Remove Claude Sonnet 3.5 v2
01 — Verdict

Gemini 2.0 Flash is our pick

Gemini 2.0 Flash is the better all-round choice, scoring 65/100 against Claude Sonnet 3.5 v2 (54) and DeepSeek-R1 (53). It leads on inputs & features and context window. DeepSeek-R1 wins on capability. The score weighs capability 67%, inputs & features 20%, context window 13%.

  • CapabilityDeepSeek-R1Capabilities Index (ECI): DeepSeek-R1 139.0 · Gemini 2.0 Flash 134.7 · Claude Sonnet 3.5 v2 133.5
  • Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · Claude Sonnet 3.5 v2 $6.00 per 1M tokens (3:1 blend) · Gemini 2.0 Flash unpriced
  • Longest contextGemini 2.0 FlashGemini 2.0 Flash 1,048,576 · Claude Sonnet 3.5 v2 200,000 · DeepSeek-R1 128,000 tokens
  • Widest inputsGemini 2.0 FlashGemini 2.0 Flash: Text, Images, PDFs, Audio, Video · DeepSeek-R1: Text · Claude Sonnet 3.5 v2: Text, Images, PDFs
  • Self-hostingDeepSeek-R1Publishes downloadable weights
How the score is built
MeasureWeightGemini 2.0 FlashDeepSeek-R1Claude Sonnet 3.5 v2
CapabilityCapabilities Index (ECI)67%596457
Inputs & features20%903560
Context window13%612432
Overall100%65/10053/10054/100

Left out because at least one model lacks the data: price. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

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

Gemini 2.0 Flash vs DeepSeek-R1 vs Claude Sonnet 3.5 v2 specifications side by side
SpecificationGemini 2.0 FlashGoogleDeepSeek-R1DeepSeekClaude Sonnet 3.5 v2Anthropic
Capability
Capabilities Index (ECI)134.7139.0 (best)133.5
ECI rank#116 of 148#104 of 148 (best)#119 of 148
GPQA DiamondGraduate-level science questions—71.7% (best)55.3%
OTIS Mock AIME 2024–2025Competition mathematics—53.3% (best)8.5%
Price per million tokens
Input—$0.70 (best)$3.00
Output—$2.60 (best)$15.00
Cached input———
Blended (3:1)—$1.18 (best)$6.00
Long-context rate—Same rateSame rate
Price source—Median of 11 providersMedian of 1 providers
Limits
Context window1,048,576 tokens (best)128,000 tokens200,000 tokens
Max output8,192 tokens32,768 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsYesNoYes
AudioYesNoNo
VideoYesNoNo
ReasoningNoYesNo
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsProprietaryOpenProprietary
API model ID———
API providers—12 (best)1
ReleasedDec 11, 2024Jan 20, 2025Oct 22, 2024
Knowledge cutoffJun 2024Jul 2024Apr 30, 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.

  • Gemini 2.0 Flash—
  • DeepSeek-R1$12.20
  • Claude Sonnet 3.5 v2$60.00
04 — Questions

Which should you choose?

Which is better: Gemini 2.0 Flash, DeepSeek-R1 or Claude Sonnet 3.5 v2?

Gemini 2.0 Flash is the better all-round choice, scoring 65/100 against Claude Sonnet 3.5 v2 (54) and DeepSeek-R1 (53). It leads on inputs & features and context window. DeepSeek-R1 wins on capability. The score weighs capability 67%, inputs & features 20%, context window 13%.

Which is cheaper, Gemini 2.0 Flash, DeepSeek-R1 or Claude Sonnet 3.5 v2?

DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). Claude Sonnet 3.5 v2 costs $3.00 input / $15.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $1.18 per million tokens for DeepSeek-R1 versus $6.00 for Claude Sonnet 3.5 v2 (5.1× as much). Gemini 2.0 Flash has no published per-token price.

Which scores higher on benchmarks?

DeepSeek-R1 scores higher on the Capabilities Index (ECI): DeepSeek-R1 139.0 (#104 of 148), Gemini 2.0 Flash 134.7 (#116 of 148) and Claude Sonnet 3.5 v2 133.5 (#119 of 148). The confidence ranges of the top two overlap (136.2–140.4 vs 124.3–136.7), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for Gemini 2.0 Flash, DeepSeek-R1 and Claude Sonnet 3.5 v2 yet, so there is no like-for-like coding score. On overall capability, DeepSeek-R1 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 2.0 Flash has the largest context window at 1,048,576 tokens, against 200,000 for Claude Sonnet 3.5 v2 and 128,000 for DeepSeek-R1. Maximum output per response: Gemini 2.0 Flash up to 8,192, DeepSeek-R1 up to 32,768, Claude Sonnet 3.5 v2 up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Gemini 2.0 Flash accepts text, images, PDFs, audio and video; DeepSeek-R1 accepts text; Claude Sonnet 3.5 v2 accepts text, images and PDFs. Gemini 2.0 Flash handles the widest range of inputs.

Are any of these open source?

DeepSeek-R1 publishes its weights and can be self-hosted; Gemini 2.0 Flash and Claude Sonnet 3.5 v2 is proprietary.

Which is newer?

DeepSeek-R1 is the newest, released Jan 20, 2025. Gemini 2.0 Flash came out Dec 11, 2024; Claude Sonnet 3.5 v2 came out Oct 22, 2024. Knowledge cutoff: Gemini 2.0 Flash Jun 2024, DeepSeek-R1 Jul 2024, Claude Sonnet 3.5 v2 Apr 30, 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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