ZMIME
Comparison · 3 models · Updated Oct 4, 2026

DeepSeek-V3.1 vs Gemini 2.5 Flash vs GLM-4.7

Gemini 2.5 Flash comes out ahead, 68 to 56 and 55 on our weighted score, though DeepSeek-V3.1 is 29% cheaper per token.

  1. DeepSeek

    DeepSeek-V3.1

    Released Aug 21, 2025

    55/100
    • ECI139.9
    • Price$0.385 / $1.25
    • Context131K
    Full specs Remove DeepSeek-V3.1
  2. Our pick

    Google

    Gemini 2.5 Flash

    Released Jun 17, 2025

    68/100
    • ECI140.8
    • Price$0.30 / $2.50
    • Context1.05M
    Full specs Remove Gemini 2.5 Flash

  3. Z.ai (Zhipu)

    GLM-4.7

    Released Dec 22, 2025

    56/100
    • ECI143.5
    • Price$0.60 / $2.20
    • Context205K
    Full specs Remove GLM-4.7
01 — Verdict

Gemini 2.5 Flash is our pick

Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against GLM-4.7 (56) and DeepSeek-V3.1 (55). It leads on inputs & features and context window. DeepSeek-V3.1 wins on price. GLM-4.7 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGLM-4.7Capabilities Index (ECI): GLM-4.7 143.5 · Gemini 2.5 Flash 140.8 · DeepSeek-V3.1 139.9
  • Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.601 · Gemini 2.5 Flash $0.85 · GLM-4.7 $1.00 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 FlashGemini 2.5 Flash 1,048,576 · GLM-4.7 204,800 · DeepSeek-V3.1 131,072 tokens
  • Widest inputsGemini 2.5 FlashDeepSeek-V3.1: Text · Gemini 2.5 Flash: Text, Images, PDFs, Audio, Video · GLM-4.7: Text
  • Self-hostingDeepSeek-V3.1 and GLM-4.7Publishes downloadable weights (MIT License)
How the score is built
MeasureWeightDeepSeek-V3.1Gemini 2.5 FlashGLM-4.7
CapabilityCapabilities Index (ECI)50%656770
Price25%605350
Inputs & features15%3510035
Context window10%246132
Overall100%55/10068/10056/100
02 — Side by side

Every spec in one table

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

DeepSeek-V3.1 vs Gemini 2.5 Flash vs GLM-4.7 specifications side by side
SpecificationDeepSeek-V3.1DeepSeekGemini 2.5 FlashGoogleGLM-4.7Z.ai (Zhipu)
Capability
Capabilities Index (ECI)139.9140.8143.5 (best)
ECI rank#100 of 148#97 of 148#84 of 148 (best)
GPQA DiamondGraduate-level science questions——83.3%
OTIS Mock AIME 2024–2025Competition mathematics——83.3%
SimpleQA VerifiedShort factual questions——32.2%
Price per million tokens
Input$0.385$0.30 (best)$0.60
Output$1.25 (best)$2.50$2.20
Cached input—$0.03 (best)$0.11
Blended (3:1)$0.601 (best)$0.85$1.00
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 8 providersOfficial Google APIOfficial Z.AI API
Limits
Context window131,072 tokens1,048,576 tokens (best)204,800 tokens
Max output8,192 tokens65,536 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoYesNo
AudioNoYesNo
VideoNoYesNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenMIT LicenseProprietaryOpen
API model ID—gemini-2.5-flashglm-4.7
API providers822 (best)20
ReleasedAug 21, 2025Jun 17, 2025Dec 22, 2025
Knowledge cutoff—Jan 2025Apr 2025
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-V3.1$6.35
  • Gemini 2.5 Flash$8.00
  • GLM-4.7$10.40
04 — Questions

Which should you choose?

Which is better: DeepSeek-V3.1, Gemini 2.5 Flash or GLM-4.7?

Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against GLM-4.7 (56) and DeepSeek-V3.1 (55). It leads on inputs & features and context window. DeepSeek-V3.1 wins on price. GLM-4.7 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek-V3.1, Gemini 2.5 Flash or GLM-4.7?

DeepSeek-V3.1 is cheaper at $0.385 input / $1.25 output per million tokens (median across 8 API providers). Gemini 2.5 Flash costs $0.30 input / $2.50 output per million tokens (official Google API price); GLM-4.7 costs $0.60 input / $2.20 output per million tokens (official Z.AI 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 $0.85 for Gemini 2.5 Flash (1.4× as much) and $1.00 for GLM-4.7 (1.7× as much).

Which scores higher on benchmarks?

GLM-4.7 scores higher on the Capabilities Index (ECI): GLM-4.7 143.5 (#84 of 148), Gemini 2.5 Flash 140.8 (#97 of 148) and DeepSeek-V3.1 139.9 (#100 of 148). The confidence ranges of the top two overlap (141.3–145.6 vs 138.5–142.3), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-V3.1, Gemini 2.5 Flash and GLM-4.7 yet, so there is no like-for-like coding score. On overall capability, GLM-4.7 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 has the largest context window at 1,048,576 tokens, against 204,800 for GLM-4.7 and 131,072 for DeepSeek-V3.1. Maximum output per response: DeepSeek-V3.1 up to 8,192, Gemini 2.5 Flash up to 65,536, GLM-4.7 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-V3.1 accepts text; Gemini 2.5 Flash accepts text, images, PDFs, audio and video; GLM-4.7 accepts text. Gemini 2.5 Flash handles the widest range of inputs.

Are any of these open source?

DeepSeek-V3.1 and GLM-4.7 publishes its weights (MIT License) and can be self-hosted; Gemini 2.5 Flash is proprietary.

Which is newer?

GLM-4.7 is the newest, released Dec 22, 2025. DeepSeek-V3.1 came out Aug 21, 2025; Gemini 2.5 Flash came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash Jan 2025, GLM-4.7 Apr 2025.

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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