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Comparison · 3 models · Updated Oct 4, 2026

Gemini 2.5 Flash vs GPT-4.1 mini vs DeepSeek-V3.1

Gemini 2.5 Flash comes out ahead, 68 to 60 and 55 on our weighted score, though DeepSeek-V3.1 is 29% cheaper per token.

  1. Our pick

    Google

    Gemini 2.5 Flash

    Released Jun 17, 2025

    68/100
    • ECI140.8
    • Price$0.30 / $2.50
    • Context1.05M
  2. OpenAI

    GPT-4.1 mini

    Released Apr 14, 2025

    60/100
    • ECI135.0
    • Price$0.40 / $1.60
    • Context1.05M
  3. DeepSeek

    DeepSeek-V3.1

    Released Aug 21, 2025

    55/100
    • ECI139.9
    • Price$0.385 / $1.25
    • Context131K
01 — Verdict

Gemini 2.5 Flash is our pick

Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against GPT-4.1 mini (60) and DeepSeek-V3.1 (55). It leads on inputs & features. DeepSeek-V3.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGemini 2.5 FlashCapabilities Index (ECI): Gemini 2.5 Flash 140.8 · DeepSeek-V3.1 139.9 · GPT-4.1 mini 135.0
  • Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.601 · GPT-4.1 mini $0.70 · Gemini 2.5 Flash $0.85 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 Flash and GPT-4.1 miniGemini 2.5 Flash 1,048,576 · GPT-4.1 mini 1,047,576 · DeepSeek-V3.1 131,072 tokens
  • Widest inputsGemini 2.5 FlashGemini 2.5 Flash: Text, Images, PDFs, Audio, Video · GPT-4.1 mini: Text, Images, PDFs · DeepSeek-V3.1: Text
  • Self-hostingDeepSeek-V3.1Publishes downloadable weights (MIT License)
How the score is built
MeasureWeightGemini 2.5 FlashGPT-4.1 miniDeepSeek-V3.1
CapabilityCapabilities Index (ECI)50%675965
Price25%535760
Inputs & features15%1007035
Context window10%616124
Overall100%68/10060/10055/100
02 — Side by side

Every spec in one table

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

Gemini 2.5 Flash vs GPT-4.1 mini vs DeepSeek-V3.1 specifications side by side
SpecificationGemini 2.5 FlashGoogleGPT-4.1 miniOpenAIDeepSeek-V3.1DeepSeek
Capability
Capabilities Index (ECI)140.8 (best)135.0139.9
ECI rank#97 of 148 (best)#115 of 148#100 of 148
GPQA DiamondGraduate-level science questions—65.9%—
FrontierMath Tiers 1–3Research-level mathematics—6.7%—
OTIS Mock AIME 2024–2025Competition mathematics—44.7%—
SimpleQA VerifiedShort factual questions—12.7%—
Price per million tokens
Input$0.30 (best)$0.40$0.385
Output$2.50$1.60$1.25 (best)
Cached input$0.03 (best)$0.10—
Blended (3:1)$0.85$0.70$0.601 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Google APIOfficial OpenAI APIMedian of 8 providers
Limits
Context window1,048,576 tokens (best)1,047,576 tokens131,072 tokens
Max output65,536 tokens (best)32,768 tokens8,192 tokens
Inputs and features
TextYesYesYes
ImagesYesYesNo
PDFsYesYesNo
AudioYesNoNo
VideoYesNoNo
ReasoningYesNoYes
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsProprietaryProprietaryOpenMIT License
API model IDgemini-2.5-flashgpt-4.1-mini—
API providers2224 (best)8
ReleasedJun 17, 2025Apr 14, 2025Aug 21, 2025
Knowledge cutoffJan 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.

  • Gemini 2.5 Flash$8.00
  • GPT-4.1 mini$7.20
  • DeepSeek-V3.1$6.35
04 — Questions

Which should you choose?

Which is better: Gemini 2.5 Flash, GPT-4.1 mini or DeepSeek-V3.1?

Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against GPT-4.1 mini (60) and DeepSeek-V3.1 (55). It leads on inputs & features. DeepSeek-V3.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemini 2.5 Flash, GPT-4.1 mini or DeepSeek-V3.1?

DeepSeek-V3.1 is cheaper at $0.385 input / $1.25 output per million tokens (median across 8 API providers). GPT-4.1 mini costs $0.40 input / $1.60 output per million tokens (official OpenAI API price); Gemini 2.5 Flash costs $0.30 input / $2.50 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $0.601 per million tokens for DeepSeek-V3.1 versus $0.70 for GPT-4.1 mini (1.2× as much) and $0.85 for Gemini 2.5 Flash (1.4× as much).

Which scores higher on benchmarks?

Gemini 2.5 Flash scores higher on the Capabilities Index (ECI): Gemini 2.5 Flash 140.8 (#97 of 148), DeepSeek-V3.1 139.9 (#100 of 148) and GPT-4.1 mini 135.0 (#115 of 148). The confidence ranges of the top two overlap (138.5–142.3 vs 136.1–143.3), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for Gemini 2.5 Flash, GPT-4.1 mini and DeepSeek-V3.1 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 mini have the largest context windows (1,048,576 and 1,047,576 tokens), against 131,072 for DeepSeek-V3.1. Maximum output per response: Gemini 2.5 Flash up to 65,536, GPT-4.1 mini up to 32,768, DeepSeek-V3.1 up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Gemini 2.5 Flash accepts text, images, PDFs, audio and video; GPT-4.1 mini accepts text, images and PDFs; DeepSeek-V3.1 accepts text. Gemini 2.5 Flash handles the widest range of inputs.

Are any of these open source?

DeepSeek-V3.1 publishes its weights (MIT License) and can be self-hosted; Gemini 2.5 Flash and GPT-4.1 mini is proprietary.

Which is newer?

DeepSeek-V3.1 is the newest, released Aug 21, 2025. Gemini 2.5 Flash came out Jun 17, 2025; GPT-4.1 mini came out Apr 14, 2025. Knowledge cutoff: Gemini 2.5 Flash Jan 2025, GPT-4.1 mini 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.