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Comparison · 2 models · Updated Oct 4, 2026

DeepSeek V4 Flash 0731 vs Gemini 3.6 Flash

Too close to call on our weighted score (DeepSeek V4 Flash 0731 76, Gemini 3.6 Flash 73). The right pick depends on what you value most.

  1. DeepSeek

    DeepSeek V4 Flash 0731

    Released Jul 31, 2026

    76/100
    • ECI154.5
    • Price$0.14 / $0.28
    • Context1M
    Full specs Remove DeepSeek V4 Flash 0731

  2. Google

    Gemini 3.6 Flash

    Released Jul 21, 2026

    73/100
    • ECI154.3
    • Price$0.75 / $3.75
    • Context1.05M
    Full specs Remove Gemini 3.6 Flash

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Too close to call

It is close. Our weighted score puts them within 3 points (DeepSeek V4 Flash 0731 76/100, Gemini 3.6 Flash 73/100), so choose by what matters most for your work: DeepSeek V4 Flash 0731 for raw capability and Gemini 3.6 Flash for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityDeepSeek V4 Flash 0731Capabilities Index (ECI): DeepSeek V4 Flash 0731 154.5 · Gemini 3.6 Flash 154.3
  • Lowest priceDeepSeek V4 Flash 0731DeepSeek V4 Flash 0731 $0.175 · Gemini 3.6 Flash $1.50 per 1M tokens (3:1 blend)
  • Longest contextGemini 3.6 FlashGemini 3.6 Flash 1,048,576 · DeepSeek V4 Flash 0731 1,000,000 tokens
  • Widest inputsGemini 3.6 FlashDeepSeek V4 Flash 0731: Text · Gemini 3.6 Flash: Text, Images, PDFs, Audio, Video
  • Self-hostingDeepSeek V4 Flash 0731Publishes downloadable weights (MIT)
How the score is built
MeasureWeightDeepSeek V4 Flash 0731Gemini 3.6 Flash
CapabilityCapabilities Index (ECI)50%8484
Price25%8642
Inputs & features15%45100
Context window10%6061
Overall100%76/10073/100
02 — Side by side

Every spec in one table

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

DeepSeek V4 Flash 0731 vs Gemini 3.6 Flash specifications side by side
SpecificationDeepSeek V4 Flash 0731DeepSeekGemini 3.6 FlashGoogle
Capability
Capabilities Index (ECI)154.5 (best)154.3
ECI rank#32 of 148 (best)#34 of 148
GPQA DiamondGraduate-level science questions91.0%94.1% (best)
FrontierMath Tiers 1–3Research-level mathematics57.5%59.0% (best)
OTIS Mock AIME 2024–2025Competition mathematics94.4% (best)94.2%
SimpleQA VerifiedShort factual questions33.6%66.2% (best)
Price per million tokens
Input$0.14 (best)$0.75
Output$0.28 (best)$3.75
Cached input—$0.075
Blended (3:1)$0.175 (best)$1.50
Long-context rateSame rateSame rate
Price sourceMedian of 48 providersOfficial Google API
Limits
Context window1,000,000 tokens1,048,576 tokens (best)
Max output384,000 tokens (best)65,536 tokens
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoYes
AudioNoYes
VideoNoYes
ReasoningYesYesminimal · low · medium · high
Tool callingYesYes
Structured outputYesYes
Availability
WeightsOpenMITProprietary
API model ID—gemini-3.6-flash
API providers49 (best)25
ReleasedJul 31, 2026Jul 21, 2026
Knowledge cutoffMay 2025Mar 2026
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 V4 Flash 0731$1.96
  • Gemini 3.6 Flash$15.00
04 — Questions

Which should you choose?

Which is better: DeepSeek V4 Flash 0731 or Gemini 3.6 Flash?

It is close. Our weighted score puts them within 3 points (DeepSeek V4 Flash 0731 76/100, Gemini 3.6 Flash 73/100), so choose by what matters most for your work: DeepSeek V4 Flash 0731 for raw capability and Gemini 3.6 Flash for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek V4 Flash 0731 or Gemini 3.6 Flash?

DeepSeek V4 Flash 0731 is cheaper at $0.14 input / $0.28 output per million tokens (median across 48 API providers). Gemini 3.6 Flash costs $0.75 input / $3.75 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for DeepSeek V4 Flash 0731 versus $1.50 for Gemini 3.6 Flash (8.6× as much).

Which scores higher on benchmarks?

DeepSeek V4 Flash 0731 scores higher on the Capabilities Index (ECI): DeepSeek V4 Flash 0731 154.5 (#32 of 148) and Gemini 3.6 Flash 154.3 (#34 of 148). The confidence ranges of the top two overlap (152.0–156.6 vs 152.6–156.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemini 3.6 Flash 94.1%, DeepSeek V4 Flash 0731 91.0%; FrontierMath Tiers 1–3 — Gemini 3.6 Flash 59.0%, DeepSeek V4 Flash 0731 57.5%; OTIS Mock AIME 2024–2025 — DeepSeek V4 Flash 0731 94.4%, Gemini 3.6 Flash 94.2%; SimpleQA Verified — Gemini 3.6 Flash 66.2%, DeepSeek V4 Flash 0731 33.6%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek V4 Flash 0731 and Gemini 3.6 Flash yet, so there is no like-for-like coding score. On overall capability, DeepSeek V4 Flash 0731 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?

Gemini 3.6 Flash has the largest context window at 1,048,576 tokens, against 1,000,000 for DeepSeek V4 Flash 0731. Maximum output per response: DeepSeek V4 Flash 0731 up to 384,000, Gemini 3.6 Flash up to 65,536 tokens.

Which can read images, PDFs, audio or video?

DeepSeek V4 Flash 0731 accepts text; Gemini 3.6 Flash accepts text, images, PDFs, audio and video. Gemini 3.6 Flash handles the widest range of inputs.

Are any of these open source?

DeepSeek V4 Flash 0731 publishes its weights (MIT) and can be self-hosted; Gemini 3.6 Flash is proprietary.

Which is newer?

DeepSeek V4 Flash 0731 is the newest, released Jul 31, 2026. Gemini 3.6 Flash came out Jul 21, 2026. Knowledge cutoff: DeepSeek V4 Flash 0731 May 2025, Gemini 3.6 Flash Mar 2026.

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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