ZMIME
Comparison · 3 models · Updated Oct 4, 2026

DeepSeek V4 Pro vs Gemini 3.6 Flash vs GLM-5V-Turbo

Gemini 3.6 Flash comes out ahead, 63 to 49 and 45 on our weighted score, and it is the cheaper option too.

  1. DeepSeek

    DeepSeek V4 Pro

    Released Apr 24, 2026

    45/100
    • ECI—
    • Price$1.32 / $3.00
    • Context1M
  2. Our pick

    Google

    Gemini 3.6 Flash

    Released Jul 21, 2026

    63/100
    • ECI154.3
    • Price$0.75 / $3.75
    • Context1.05M
  3. Z.ai (Zhipu)

    GLM-5V-Turbo

    Released Apr 1, 2026

    49/100
    • ECI—
    • Price$1.20 / $4.00
    • Context200K
01 — Verdict

Gemini 3.6 Flash is our pick

Gemini 3.6 Flash is the better all-round choice, scoring 63/100 against GLM-5V-Turbo (49) and DeepSeek V4 Pro (45). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceGemini 3.6 FlashGemini 3.6 Flash $1.50 · DeepSeek V4 Pro $1.74 · GLM-5V-Turbo $1.90 per 1M tokens (3:1 blend)
  • Longest contextGemini 3.6 FlashGemini 3.6 Flash 1,048,576 · DeepSeek V4 Pro 1,000,000 · GLM-5V-Turbo 200,000 tokens
  • Widest inputsGemini 3.6 FlashDeepSeek V4 Pro: Text · Gemini 3.6 Flash: Text, Images, PDFs, Audio, Video · GLM-5V-Turbo: Text, Images, PDFs, Video
  • Self-hostingDeepSeek V4 ProPublishes downloadable weights
How the score is built
MeasureWeightDeepSeek V4 ProGemini 3.6 FlashGLM-5V-Turbo
Price50%384237
Inputs & features30%4510080
Context window20%606132
Overall100%45/10063/10049/100

Left out because at least one model lacks the data: capability. 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.

DeepSeek V4 Pro vs Gemini 3.6 Flash vs GLM-5V-Turbo specifications side by side
SpecificationDeepSeek V4 ProDeepSeekGemini 3.6 FlashGoogleGLM-5V-TurboZ.ai (Zhipu)
Capability
Capabilities Index (ECI)—154.3—
ECI rank—#34 of 148—
GPQA DiamondGraduate-level science questions—94.1%—
FrontierMath Tiers 1–3Research-level mathematics—59.0%—
OTIS Mock AIME 2024–2025Competition mathematics—94.2%—
SimpleQA VerifiedShort factual questions—66.2%—
Price per million tokens
Input$1.32$0.75 (best)$1.20
Output$3.00 (best)$3.75$4.00
Cached input—$0.075 (best)$0.24
Blended (3:1)$1.74$1.50 (best)$1.90
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 49 providersOfficial Google APIOfficial Z.AI API
Limits
Context window1,000,000 tokens1,048,576 tokens (best)200,000 tokens
Max output384,000 tokens (best)65,536 tokens131,072 tokens
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoYesYes
AudioNoYesNo
VideoNoYesYes
ReasoningYesYesminimal · low · medium · highYes
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsOpenProprietaryProprietary
API model ID—gemini-3.6-flashglm-5v-turbo
API providers52 (best)2514
ReleasedApr 24, 2026Jul 21, 2026Apr 1, 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 Pro$19.20
  • Gemini 3.6 Flash$15.00
  • GLM-5V-Turbo$20.00
04 — Questions

Which should you choose?

Which is better: DeepSeek V4 Pro, Gemini 3.6 Flash or GLM-5V-Turbo?

Gemini 3.6 Flash is the better all-round choice, scoring 63/100 against GLM-5V-Turbo (49) and DeepSeek V4 Pro (45). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, DeepSeek V4 Pro, Gemini 3.6 Flash or GLM-5V-Turbo?

Gemini 3.6 Flash is cheaper at $0.75 input / $3.75 output per million tokens (official Google API price). DeepSeek V4 Pro costs $1.32 input / $3.00 output per million tokens (median across 49 API providers); GLM-5V-Turbo costs $1.20 input / $4.00 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $1.50 per million tokens for Gemini 3.6 Flash versus $1.74 for DeepSeek V4 Pro (1.2× as much) and $1.90 for GLM-5V-Turbo (1.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. DeepSeek V4 Pro has not been scored yet, Gemini 3.6 Flash has an ECI of 154.3 and GLM-5V-Turbo has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek V4 Pro, Gemini 3.6 Flash and GLM-5V-Turbo yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three 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 Pro and 200,000 for GLM-5V-Turbo. Maximum output per response: DeepSeek V4 Pro up to 384,000, Gemini 3.6 Flash up to 65,536, GLM-5V-Turbo up to 131,072 tokens.

Which can read images, PDFs, audio or video?

DeepSeek V4 Pro accepts text; Gemini 3.6 Flash accepts text, images, PDFs, audio and video; GLM-5V-Turbo accepts text, images, PDFs and video. Gemini 3.6 Flash handles the widest range of inputs.

Are any of these open source?

DeepSeek V4 Pro publishes its weights and can be self-hosted; Gemini 3.6 Flash and GLM-5V-Turbo is proprietary.

Which is newer?

Gemini 3.6 Flash is the newest, released Jul 21, 2026. DeepSeek V4 Pro came out Apr 24, 2026; GLM-5V-Turbo came out Apr 1, 2026. Knowledge cutoff: DeepSeek V4 Pro 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.