ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Kimi K2 Thinking vs Mistral Small 3.1 24B vs Qwen3.5 Plus

Qwen3.5 Plus comes out ahead, 66 to 58 and 55 on our weighted score, though Mistral Small 3.1 24B is 3.2× cheaper per token.

  1. Moonshot AI

    Kimi K2 Thinking

    Released Nov 6, 2025

    58/100
    • ECI146.0
    • Price$0.60 / $2.50
    • Context262K
  2. Mistral AI

    Mistral Small 3.1 24B

    Released Mar 17, 2025

    55/100
    • ECI127.5
    • Price$0.229 / $0.436
    • Context128K
  3. Our pick

    Alibaba (Qwen)

    Qwen3.5 Plus

    Released Feb 16, 2026

    66/100
    • ECI146.8
    • Price$0.40 / $2.40
    • Context1M
01 — Verdict

Qwen3.5 Plus is our pick

Qwen3.5 Plus is the better all-round choice, scoring 66/100 against Kimi K2 Thinking (58) and Mistral Small 3.1 24B (55). It leads on inputs & features and context window. Mistral Small 3.1 24B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.5 PlusCapabilities Index (ECI): Qwen3.5 Plus 146.8 · Kimi K2 Thinking 146.0 · Mistral Small 3.1 24B 127.5
  • Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · Qwen3.5 Plus $0.90 · Kimi K2 Thinking $1.07 per 1M tokens (3:1 blend)
  • Longest contextQwen3.5 PlusQwen3.5 Plus 1,000,000 · Kimi K2 Thinking 262,144 · Mistral Small 3.1 24B 128,000 tokens
  • Widest inputsQwen3.5 PlusKimi K2 Thinking: Text · Mistral Small 3.1 24B: Text, Images · Qwen3.5 Plus: Text, Images, Video
  • Self-hostingKimi K2 Thinking and Mistral Small 3.1 24BPublishes downloadable weights
How the score is built
MeasureWeightKimi K2 ThinkingMistral Small 3.1 24BQwen3.5 Plus
CapabilityCapabilities Index (ECI)50%735074
Price25%487652
Inputs & features15%356070
Context window10%372460
Overall100%58/10055/10066/100
02 — Side by side

Every spec in one table

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

Kimi K2 Thinking vs Mistral Small 3.1 24B vs Qwen3.5 Plus specifications side by side
SpecificationKimi K2 ThinkingMoonshot AIMistral Small 3.1 24BMistral AIQwen3.5 PlusAlibaba (Qwen)
Capability
Capabilities Index (ECI)146.0127.5146.8 (best)
ECI rank#72 of 148#132 of 148#65 of 148 (best)
GPQA DiamondGraduate-level science questions84.2%47.5%84.9% (best)
OTIS Mock AIME 2024–2025Competition mathematics83.1%5.8%86.7% (best)
SimpleQA VerifiedShort factual questions——25.4%
Price per million tokens
Input$0.60$0.229 (best)$0.40
Output$2.50$0.436 (best)$2.40
Cached input———
Blended (3:1)$1.07$0.281 (best)$0.90
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 10 providersMedian of 2 providersOfficial Alibaba API
Limits
Context window262,144 tokens128,000 tokens1,000,000 tokens (best)
Max output262,144 tokens (best)16,384 tokens65,536 tokens
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoYes
ReasoningYesNoYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenOpenProprietary
API model ID——qwen3.5-plus
API providers10 (best)210 (best)
ReleasedNov 6, 2025Mar 17, 2025Feb 16, 2026
Knowledge cutoffAug 2024Jun 2024Apr 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.

  • Kimi K2 Thinking$11.00
  • Mistral Small 3.1 24B$3.16
  • Qwen3.5 Plus$8.80
04 — Questions

Which should you choose?

Which is better: Kimi K2 Thinking, Mistral Small 3.1 24B or Qwen3.5 Plus?

Qwen3.5 Plus is the better all-round choice, scoring 66/100 against Kimi K2 Thinking (58) and Mistral Small 3.1 24B (55). It leads on inputs & features and context window. Mistral Small 3.1 24B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Kimi K2 Thinking, Mistral Small 3.1 24B or Qwen3.5 Plus?

Mistral Small 3.1 24B is cheaper at $0.229 input / $0.436 output per million tokens (median across 2 API providers). Qwen3.5 Plus costs $0.40 input / $2.40 output per million tokens (official Alibaba API price); Kimi K2 Thinking costs $0.60 input / $2.50 output per million tokens (median across 10 API providers). At a typical mix of three input tokens to one output token, that is $0.281 per million tokens for Mistral Small 3.1 24B versus $0.90 for Qwen3.5 Plus (3.2× as much) and $1.07 for Kimi K2 Thinking (3.8× as much).

Which scores higher on benchmarks?

Qwen3.5 Plus scores higher on the Capabilities Index (ECI): Qwen3.5 Plus 146.8 (#65 of 148), Kimi K2 Thinking 146.0 (#72 of 148) and Mistral Small 3.1 24B 127.5 (#132 of 148). The confidence ranges of the top two overlap (144.6–148.1 vs 143.4–147.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 Plus 84.9%, Kimi K2 Thinking 84.2%, Mistral Small 3.1 24B 47.5%; OTIS Mock AIME 2024–2025 — Qwen3.5 Plus 86.7%, Kimi K2 Thinking 83.1%, Mistral Small 3.1 24B 5.8%.

Which is better for coding?

There are no published SWE-bench Verified results for Kimi K2 Thinking, Mistral Small 3.1 24B and Qwen3.5 Plus yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 Plus 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?

Qwen3.5 Plus has the largest context window at 1,000,000 tokens, against 262,144 for Kimi K2 Thinking and 128,000 for Mistral Small 3.1 24B. Maximum output per response: Kimi K2 Thinking up to 262,144, Mistral Small 3.1 24B up to 16,384, Qwen3.5 Plus up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Kimi K2 Thinking accepts text; Mistral Small 3.1 24B accepts text and images; Qwen3.5 Plus accepts text, images and video. Qwen3.5 Plus handles the widest range of inputs.

Are any of these open source?

Kimi K2 Thinking and Mistral Small 3.1 24B publishes its weights and can be self-hosted; Qwen3.5 Plus is proprietary.

Which is newer?

Qwen3.5 Plus is the newest, released Feb 16, 2026. Kimi K2 Thinking came out Nov 6, 2025; Mistral Small 3.1 24B came out Mar 17, 2025. Knowledge cutoff: Kimi K2 Thinking Aug 2024, Mistral Small 3.1 24B Jun 2024, Qwen3.5 Plus 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.