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Comparison · 3 models · Updated Nov 2, 2026

Grok 4 Fast Non Reasoning vs Qwen3 VL 30B A3B Instruct vs GLM-4.6V-Flash

Grok 4 Fast Non Reasoning comes out ahead, 72 to 63 and 62 on our weighted score, though GLM-4.6V-Flash is 5% cheaper per token.

  1. Our pick

    xAI

    Grok 4 Fast Non Reasoning

    Released Dec 18, 2025

    72/100
    • ECI—
    • Price$0.20 / $0.50
    • Context2M
  2. Alibaba (Qwen)

    Qwen3 VL 30B A3B Instruct

    Released Oct 4, 2025

    62/100
    • ECI—
    • Price$0.15 / $0.60
    • Context262K
  3. Z.ai (Zhipu)

    GLM-4.6V-Flash

    Released Dec 8, 2025

    63/100
    • ECI—
    • Price$0.161 / $0.559
    • Context128K
01 — Verdict

Grok 4 Fast Non Reasoning is our pick

Grok 4 Fast Non Reasoning is the better all-round choice, scoring 72/100 against GLM-4.6V-Flash (63) and Qwen3 VL 30B A3B Instruct (62). It leads on context window. 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 priceGLM-4.6V-FlashGLM-4.6V-Flash $0.261 · Qwen3 VL 30B A3B Instruct $0.263 · Grok 4 Fast Non Reasoning $0.275 per 1M tokens (3:1 blend)
  • Longest contextGrok 4 Fast Non ReasoningGrok 4 Fast Non Reasoning 2,000,000 · Qwen3 VL 30B A3B Instruct 262,144 · GLM-4.6V-Flash 128,000 tokens
  • Widest inputsGrok 4 Fast Non ReasoningGrok 4 Fast Non Reasoning: Text, Images, Audio, Video · Qwen3 VL 30B A3B Instruct: Text, Images, Video · GLM-4.6V-Flash: Text, Images, Video
  • Self-hostingQwen3 VL 30B A3B Instruct and GLM-4.6V-FlashPublishes downloadable weights (Apache-2.0)
How the score is built
MeasureWeightGrok 4 Fast Non ReasoningQwen3 VL 30B A3B InstructGLM-4.6V-Flash
Price50%737474
Inputs & features30%706070
Context window20%723724
Overall100%72/10062/10063/100

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.

Grok 4 Fast Non Reasoning vs Qwen3 VL 30B A3B Instruct vs GLM-4.6V-Flash specifications side by side
SpecificationGrok 4 Fast Non ReasoningxAIQwen3 VL 30B A3B InstructAlibaba (Qwen)GLM-4.6V-FlashZ.ai (Zhipu)
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.20$0.15 (best)$0.161
Output$0.50 (best)$0.60$0.559
Cached input———
Blended (3:1)$0.275$0.263$0.261 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 7 providersMedian of 13 providersMedian of 2 providers
Limits
Context window2,000,000 tokens (best)262,144 tokens128,000 tokens
Max output2,000,000 tokens (best)32,768 tokens32,768 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioYesNoNo
VideoYesYesYes
ReasoningNoNoYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsProprietaryOpenApache-2.0Open
API model ID——glm-4.6v-flash
API providers813 (best)6
ReleasedDec 18, 2025Oct 4, 2025Dec 8, 2025
Knowledge cutoff———
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.

  • Grok 4 Fast Non Reasoning$3.00
  • Qwen3 VL 30B A3B Instruct$2.70
  • GLM-4.6V-Flash$2.73
04 — Questions

Which should you choose?

Which is better: Grok 4 Fast Non Reasoning, Qwen3 VL 30B A3B Instruct or GLM-4.6V-Flash?

Grok 4 Fast Non Reasoning is the better all-round choice, scoring 72/100 against GLM-4.6V-Flash (63) and Qwen3 VL 30B A3B Instruct (62). It leads on context window. 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, Grok 4 Fast Non Reasoning, Qwen3 VL 30B A3B Instruct or GLM-4.6V-Flash?

GLM-4.6V-Flash is cheaper at $0.161 input / $0.559 output per million tokens (median across 2 API providers; free on Z.AI). Qwen3 VL 30B A3B Instruct costs $0.15 input / $0.60 output per million tokens (median across 13 API providers); Grok 4 Fast Non Reasoning costs $0.20 input / $0.50 output per million tokens (median across 7 API providers). At a typical mix of three input tokens to one output token, that is $0.261 per million tokens for GLM-4.6V-Flash versus $0.263 for Qwen3 VL 30B A3B Instruct (1× as much) and $0.275 for Grok 4 Fast Non Reasoning (1.1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Grok 4 Fast Non Reasoning has not been scored yet, Qwen3 VL 30B A3B Instruct has not been scored yet and GLM-4.6V-Flash has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Grok 4 Fast Non Reasoning, Qwen3 VL 30B A3B Instruct and GLM-4.6V-Flash 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?

Grok 4 Fast Non Reasoning has the largest context window at 2,000,000 tokens, against 262,144 for Qwen3 VL 30B A3B Instruct and 128,000 for GLM-4.6V-Flash. Maximum output per response: Grok 4 Fast Non Reasoning up to 2,000,000, Qwen3 VL 30B A3B Instruct up to 32,768, GLM-4.6V-Flash up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Grok 4 Fast Non Reasoning accepts text, images, audio and video; Qwen3 VL 30B A3B Instruct accepts text, images and video; GLM-4.6V-Flash accepts text, images and video. Grok 4 Fast Non Reasoning handles the widest range of inputs.

Are any of these open source?

Qwen3 VL 30B A3B Instruct and GLM-4.6V-Flash publishes its weights (Apache-2.0) and can be self-hosted; Grok 4 Fast Non Reasoning is proprietary.

Which is newer?

Grok 4 Fast Non Reasoning is the newest, released Dec 18, 2025. GLM-4.6V-Flash came out Dec 8, 2025; Qwen3 VL 30B A3B Instruct came out Oct 4, 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 Nov 2, 2026.