ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Mistral Large 4 vs Inkling Small vs Qwen3.8 27B

Too close to call on our weighted score (Inkling Small 68, Mistral Large 4 67, Qwen3.8 27B 66). The right pick depends on what you value most.

  1. Mistral AI

    Mistral Large 4

    Released Oct 6, 2026NewBeta

    67/100
    • ECI150.6
    • Price$0.70 / $2.10
    • Context1.05M
  2. Thinking Machines

    Inkling Small

    Released Jul 30, 2026

    68/100
    • ECI150.5
    • Price$0.58 / $1.44
    • Context1.05M
  3. Alibaba (Qwen)

    Qwen3.8 27B

    Released Aug 14, 2026

    66/100
    • ECI151.8
    • Price$0.40 / $2.55
    • Context262K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Inkling Small 68/100, Mistral Large 4 67/100, Qwen3.8 27B 66/100), so choose by what matters most for your work: Qwen3.8 27B for raw capability and Inkling Small on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.8 27BCapabilities Index (ECI): Qwen3.8 27B 151.8 · Mistral Large 4 150.6 · Inkling Small 150.5
  • Lowest priceInkling SmallInkling Small $0.795 · Qwen3.8 27B $0.938 · Mistral Large 4 $1.05 per 1M tokens (3:1 blend)
  • Longest contextMistral Large 4 and Inkling SmallMistral Large 4 1,048,576 · Inkling Small 1,048,576 · Qwen3.8 27B 262,144 tokens
  • Widest inputsInkling Small and Qwen3.8 27BMistral Large 4: Text, Images · Inkling Small: Text, Images, Audio · Qwen3.8 27B: Text, Images, Video
  • Self-hostingInkling Small and Qwen3.8 27BPublishes downloadable weights (Apache-2.0)
How the score is built
MeasureWeightMistral Large 4Inkling SmallQwen3.8 27B
CapabilityCapabilities Index (ECI)50%777779
Price25%475249
Inputs & features15%707070
Context window10%616137
Overall100%67/10068/10066/100
02 — Side by side

Every spec in one table

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

Mistral Large 4 vs Inkling Small vs Qwen3.8 27B specifications side by side
SpecificationMistral Large 4Mistral AIInkling SmallThinking MachinesQwen3.8 27BAlibaba (Qwen)
Capability
Capabilities Index (ECI)150.6150.5151.8 (best)
ECI rank#57 of 165#58 of 165#54 of 165 (best)
GPQA DiamondGraduate-level science questions88.1%88.5% (best)—
FrontierMath Tiers 1–3Research-level mathematics58.6% (best)46.3%—
OTIS Mock AIME 2024–2025Competition mathematics98.3% (best)90.0%—
SimpleQA VerifiedShort factual questions20.0% (best)19.1%—
Price per million tokens
Input$0.70$0.58$0.40 (best)
Output$2.10$1.44 (best)$2.55
Cached input$0.07 (best)$0.116—
Blended (3:1)$1.05$0.795 (best)$0.938
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial Thinking Machines APIMedian of 49 providers
Limits
Context window1,048,576 tokens (best)1,048,576 tokens (best)262,144 tokens
Max output262,144 tokens1,048,576 tokens (best)32,768 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioNoYesNo
VideoNoNoYes
ReasoningYeslow · medium · highYeslow · medium · high · xhigh · maxYes
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsProprietaryOpenApache-2.0Open
API model IDmistral-large-4thinkingmachines/Inkling-Small—
API providers151253 (best)
ReleasedOct 6, 2026Jul 30, 2026Aug 14, 2026
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.

  • Mistral Large 4$11.20
  • Inkling Small$8.68
  • Qwen3.8 27B$9.10
04 — Questions

Which should you choose?

Which is better: Mistral Large 4, Inkling Small or Qwen3.8 27B?

It is close. Our weighted score puts them within 1 points (Inkling Small 68/100, Mistral Large 4 67/100, Qwen3.8 27B 66/100), so choose by what matters most for your work: Qwen3.8 27B for raw capability and Inkling Small on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Large 4, Inkling Small or Qwen3.8 27B?

Inkling Small is cheaper at $0.58 input / $1.44 output per million tokens (official Thinking Machines API price). Qwen3.8 27B costs $0.40 input / $2.55 output per million tokens (median across 49 API providers); Mistral Large 4 costs $0.70 input / $2.10 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.795 per million tokens for Inkling Small versus $0.938 for Qwen3.8 27B (1.2× as much) and $1.05 for Mistral Large 4 (1.3× as much).

Which scores higher on benchmarks?

Qwen3.8 27B scores higher on the Capabilities Index (ECI): Qwen3.8 27B 151.8 (#54 of 165), Mistral Large 4 150.6 (#57 of 165) and Inkling Small 150.5 (#58 of 165). The confidence ranges of the top two overlap (149.9–153.6 vs 147.4–153.5), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Large 4, Inkling Small and Qwen3.8 27B yet, so there is no like-for-like coding score. On overall capability, Qwen3.8 27B 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?

Mistral Large 4 and Inkling Small have the largest context windows (1,048,576 and 1,048,576 tokens), against 262,144 for Qwen3.8 27B. Maximum output per response: Mistral Large 4 up to 262,144, Inkling Small up to 1,048,576, Qwen3.8 27B up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Mistral Large 4 accepts text and images; Inkling Small accepts text, images and audio; Qwen3.8 27B accepts text, images and video. Inkling Small handles the widest range of inputs.

Are any of these open source?

Inkling Small and Qwen3.8 27B publishes its weights (Apache-2.0) and can be self-hosted; Mistral Large 4 is proprietary.

Which is newer?

Mistral Large 4 is the newest, released Oct 6, 2026. Qwen3.8 27B came out Aug 14, 2026; Inkling Small came out Jul 30, 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 Nov 2, 2026.