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Comparison · 2 models · Updated Nov 2, 2026

DeepSeek V4.1 Flash 1017 vs Gemini 4 Argon

DeepSeek V4.1 Flash 1017 comes out ahead, 79 to 74 on our weighted score, and it is the cheaper option too.

  1. Our pick

    DeepSeek

    DeepSeek V4.1 Flash 1017

    Released Oct 17, 2026New

    79/100
    • ECI158.8
    • Price$0.15 / $0.60
    • Context1M
    Full specs Remove DeepSeek V4.1 Flash 1017

  2. Google

    Gemini 4 Argon

    Released Oct 13, 2026New

    74/100
    • ECI166.1
    • Price$2.00 / $10.00
    • Context1.05M
    Full specs Remove Gemini 4 Argon

  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 Gemini 4 Argon (74). It leads on price. Gemini 4 Argon wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGemini 4 ArgonCapabilities Index (ECI): Gemini 4 Argon 166.1 · DeepSeek V4.1 Flash 1017 158.8
  • Lowest priceDeepSeek V4.1 Flash 1017DeepSeek V4.1 Flash 1017 $0.263 · Gemini 4 Argon $4.00 per 1M tokens (3:1 blend)
  • Longest contextGemini 4 ArgonGemini 4 Argon 1,048,576 · DeepSeek V4.1 Flash 1017 1,000,000 tokens
  • Widest inputsGemini 4 ArgonDeepSeek V4.1 Flash 1017: Text, Images · Gemini 4 Argon: Text, Images, PDFs, Audio, Video
  • Self-hostingDeepSeek V4.1 Flash 1017Publishes downloadable weights (MIT)
How the score is built
MeasureWeightDeepSeek V4.1 Flash 1017Gemini 4 Argon
CapabilityCapabilities Index (ECI)50%8796
Price25%7420
Inputs & features15%70100
Context window10%6061
Overall100%79/10074/100
02 — Side by side

Every spec in one table

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

DeepSeek V4.1 Flash 1017 vs Gemini 4 Argon specifications side by side
SpecificationDeepSeek V4.1 Flash 1017DeepSeekGemini 4 ArgonGoogle
Capability
Capabilities Index (ECI)158.8166.1 (best)
ECI rank#19 of 165#7 of 165 (best)
GPQA DiamondGraduate-level science questions93.2%96.4% (best)
FrontierMath Tiers 1–3Research-level mathematics71.2%86.0% (best)
OTIS Mock AIME 2024–2025Competition mathematics99.4%100% (best)
SimpleQA VerifiedShort factual questions42.5%76.0% (best)
Price per million tokens
Input$0.15 (best)$2.00
Output$0.60 (best)$10.00
Cached input$0.003 (best)$0.10
Blended (3:1)$0.263 (best)$4.00
Long-context rateSame rateSame rate
Price sourceOfficial DeepSeek APIOfficial Google API
Limits
Context window1,000,000 tokens1,048,576 tokens (best)
Max output384,000 tokens (best)65,536 tokens
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoYes
AudioNoYes
VideoNoYes
ReasoningYeslow · high · maxYeslow · medium · high
Tool callingYesYes
Structured outputYesYes
Availability
WeightsOpenMITProprietary
API model IDdeepseek-flashgemini-4-argon
API providers40 (best)24
ReleasedOct 17, 2026Oct 13, 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 V4.1 Flash 1017$2.70
  • Gemini 4 Argon$40.00
04 — Questions

Which should you choose?

Which is better: DeepSeek V4.1 Flash 1017 or Gemini 4 Argon?

DeepSeek V4.1 Flash 1017 is the better all-round choice, scoring 79/100 against Gemini 4 Argon (74). It leads on price. Gemini 4 Argon wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek V4.1 Flash 1017 or Gemini 4 Argon?

DeepSeek V4.1 Flash 1017 is cheaper at $0.15 input / $0.60 output per million tokens (official DeepSeek API price). Gemini 4 Argon costs $2.00 input / $10.00 output per million tokens (official Google 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 $4.00 for Gemini 4 Argon (15× as much).

Which scores higher on benchmarks?

Gemini 4 Argon scores higher on the Capabilities Index (ECI): Gemini 4 Argon 166.1 (#7 of 165) and DeepSeek V4.1 Flash 1017 158.8 (#19 of 165). Their confidence ranges do not overlap (163.1–170.3 vs 156.7–162.2), so the gap is a real one. On individual benchmarks: GPQA Diamond — Gemini 4 Argon 96.4%, DeepSeek V4.1 Flash 1017 93.2%; FrontierMath Tiers 1–3 — Gemini 4 Argon 86.0%, DeepSeek V4.1 Flash 1017 71.2%; OTIS Mock AIME 2024–2025 — Gemini 4 Argon 100%, DeepSeek V4.1 Flash 1017 99.4%; SimpleQA Verified — Gemini 4 Argon 76.0%, DeepSeek V4.1 Flash 1017 42.5%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek V4.1 Flash 1017 and Gemini 4 Argon yet, so there is no like-for-like coding score. On overall capability, Gemini 4 Argon 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 4 Argon has the largest context window at 1,048,576 tokens, against 1,000,000 for DeepSeek V4.1 Flash 1017. Maximum output per response: DeepSeek V4.1 Flash 1017 up to 384,000, Gemini 4 Argon up to 65,536 tokens.

Which can read images, PDFs, audio or video?

DeepSeek V4.1 Flash 1017 accepts text and images; Gemini 4 Argon accepts text, images, PDFs, audio and video. Gemini 4 Argon 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; Gemini 4 Argon is proprietary.

Which is newer?

DeepSeek V4.1 Flash 1017 is the newest, released Oct 17, 2026. Gemini 4 Argon came out Oct 13, 2026. Knowledge cutoff: DeepSeek V4.1 Flash 1017 May 2025, Gemini 4 Argon 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 Nov 2, 2026.

05 — Keep comparing

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