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Comparison · 2 models · Updated Nov 2, 2026

Qwen3 VL 235B A22B Thinking vs Kimi K2 Instruct 0905

Qwen3 VL 235B A22B Thinking comes out ahead, 44 to 38 on our weighted score, though Kimi K2 Instruct 0905 is 21% cheaper per token.

  1. Our pick

    Alibaba (Qwen)

    Qwen3 VL 235B A22B Thinking

    Released Sep 23, 2025

    44/100
    • ECI—
    • Price$0.50 / $3.95
    • Context131K
    Full specs Remove Qwen3 VL 235B A22B Thinking

  2. Moonshot AI

    Kimi K2 Instruct 0905

    Released Sep 5, 2025

    38/100
    • ECI—
    • Price$0.60 / $2.50
    • Context262K
    Full specs Remove Kimi K2 Instruct 0905

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen3 VL 235B A22B Thinking is our pick

Qwen3 VL 235B A22B Thinking is the better all-round choice, scoring 44/100 against Kimi K2 Instruct 0905 (38). It leads on inputs & features. Kimi K2 Instruct 0905 wins on price and 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 priceKimi K2 Instruct 0905Kimi K2 Instruct 0905 $1.07 · Qwen3 VL 235B A22B Thinking $1.36 per 1M tokens (3:1 blend)
  • Longest contextKimi K2 Instruct 0905Kimi K2 Instruct 0905 262,144 · Qwen3 VL 235B A22B Thinking 131,072 tokens
  • Widest inputsQwen3 VL 235B A22B ThinkingQwen3 VL 235B A22B Thinking: Text, Images · Kimi K2 Instruct 0905: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3 VL 235B A22B ThinkingKimi K2 Instruct 0905
Price50%4246
Inputs & features30%6025
Context window20%2537
Overall100%44/10038/100

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.

Qwen3 VL 235B A22B Thinking vs Kimi K2 Instruct 0905 specifications side by side
SpecificationQwen3 VL 235B A22B ThinkingAlibaba (Qwen)Kimi K2 Instruct 0905Moonshot AI
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.50 (best)$0.60
Output$3.95$2.50 (best)
Cached input——
Blended (3:1)$1.36$1.07 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 5 providersMedian of 12 providers
Limits
Context window131,072 tokens262,144 tokens (best)
Max output32,768 tokens98,304 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpenModified MIT
API model ID——
API providers513 (best)
ReleasedSep 23, 2025Sep 5, 2025
Knowledge cutoffMar 31, 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.

  • Qwen3 VL 235B A22B Thinking$12.90
  • Kimi K2 Instruct 0905$11.00
04 — Questions

Which should you choose?

Which is better: Qwen3 VL 235B A22B Thinking or Kimi K2 Instruct 0905?

Qwen3 VL 235B A22B Thinking is the better all-round choice, scoring 44/100 against Kimi K2 Instruct 0905 (38). It leads on inputs & features. Kimi K2 Instruct 0905 wins on price and 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, Qwen3 VL 235B A22B Thinking or Kimi K2 Instruct 0905?

Kimi K2 Instruct 0905 is cheaper at $0.60 input / $2.50 output per million tokens (median across 12 API providers). Qwen3 VL 235B A22B Thinking costs $0.50 input / $3.95 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $1.07 per million tokens for Kimi K2 Instruct 0905 versus $1.36 for Qwen3 VL 235B A22B Thinking (1.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Qwen3 VL 235B A22B Thinking has not been scored yet and Kimi K2 Instruct 0905 has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 VL 235B A22B Thinking and Kimi K2 Instruct 0905 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

Kimi K2 Instruct 0905 has the largest context window at 262,144 tokens, against 131,072 for Qwen3 VL 235B A22B Thinking. Maximum output per response: Qwen3 VL 235B A22B Thinking up to 32,768, Kimi K2 Instruct 0905 up to 98,304 tokens.

Which can read images, PDFs, audio or video?

Qwen3 VL 235B A22B Thinking accepts text and images; Kimi K2 Instruct 0905 accepts text. Qwen3 VL 235B A22B Thinking handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights (Modified MIT), so you can self-host them.

Which is newer?

Qwen3 VL 235B A22B Thinking is the newest, released Sep 23, 2025. Kimi K2 Instruct 0905 came out Sep 5, 2025. Knowledge cutoff: Qwen3 VL 235B A22B Thinking Mar 31, 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.

05 — Keep comparing

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