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Comparison · 3 models · Updated Nov 2, 2026

DeepSeek-V3.1 vs GPT OSS 120B vs Kimi K2 Instruct

Too close to call on our weighted score (GPT OSS 120B 58, DeepSeek-V3.1 56, Kimi K2 Instruct 50). The right pick depends on what you value most.

  1. DeepSeek

    DeepSeek-V3.1

    Released Aug 21, 2025

    56/100
    • ECI139.8
    • Price$0.27 / $1.00
    • Context131K
    Full specs Remove DeepSeek-V3.1

  2. OpenAI

    GPT OSS 120B

    Released Aug 5, 2025

    58/100
    • ECI139.8
    • Price$0.15 / $0.60
    • Context131K
    Full specs Remove GPT OSS 120B

  3. Moonshot AI

    Kimi K2 Instruct

    Released Jul 11, 2025

    50/100
    • ECI139.9
    • Price$0.57 / $2.30
    • Context131K
    Full specs Remove Kimi K2 Instruct
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 3 points (GPT OSS 120B 58/100, DeepSeek-V3.1 56/100, Kimi K2 Instruct 50/100), so choose by what matters most for your work: Kimi K2 Instruct for raw capability and GPT OSS 120B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityKimi K2 InstructCapabilities Index (ECI): Kimi K2 Instruct 139.9 · DeepSeek-V3.1 139.8 · GPT OSS 120B 139.8
  • Lowest priceGPT OSS 120BGPT OSS 120B $0.263 · DeepSeek-V3.1 $0.453 · Kimi K2 Instruct $1.00 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameDeepSeek-V3.1 131,072 · GPT OSS 120B 131,072 · Kimi K2 Instruct 131,072 tokens
  • Widest inputsSame inputsDeepSeek-V3.1: Text · GPT OSS 120B: Text · Kimi K2 Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightDeepSeek-V3.1GPT OSS 120BKimi K2 Instruct
CapabilityCapabilities Index (ECI)50%646464
Price25%637448
Inputs & features15%353525
Context window10%252525
Overall100%56/10058/10050/100
02 — Side by side

Every spec in one table

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

DeepSeek-V3.1 vs GPT OSS 120B vs Kimi K2 Instruct specifications side by side
SpecificationDeepSeek-V3.1DeepSeekGPT OSS 120BOpenAIKimi K2 InstructMoonshot AI
Capability
Capabilities Index (ECI)139.8139.8139.9 (best)
ECI rank#113 of 165#114 of 165#112 of 165 (best)
GPQA DiamondGraduate-level science questions—75.8%—
OTIS Mock AIME 2024–2025Competition mathematics—88.9%—
Price per million tokens
Input$0.27$0.15 (best)$0.57
Output$1.00$0.60 (best)$2.30
Cached input———
Blended (3:1)$0.453$0.263 (best)$1.00
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 19 providersMedian of 65 providersMedian of 11 providers
Limits
Context window131,072 tokens131,072 tokens131,072 tokens
Max output8,192 tokens32,768 tokens (best)32,768 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenMIT LicenseOpenOpenModified MIT
API model ID———
API providers1967 (best)11
ReleasedAug 21, 2025Aug 5, 2025Jul 11, 2025
Knowledge cutoff—Jun 2024—
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-V3.1$4.70
  • GPT OSS 120B$2.70
  • Kimi K2 Instruct$10.30
04 — Questions

Which should you choose?

Which is better: DeepSeek-V3.1, GPT OSS 120B or Kimi K2 Instruct?

It is close. Our weighted score puts them within 3 points (GPT OSS 120B 58/100, DeepSeek-V3.1 56/100, Kimi K2 Instruct 50/100), so choose by what matters most for your work: Kimi K2 Instruct for raw capability and GPT OSS 120B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek-V3.1, GPT OSS 120B or Kimi K2 Instruct?

GPT OSS 120B is cheaper at $0.15 input / $0.60 output per million tokens (median across 65 API providers). DeepSeek-V3.1 costs $0.27 input / $1.00 output per million tokens (median across 19 API providers); Kimi K2 Instruct costs $0.57 input / $2.30 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for GPT OSS 120B versus $0.453 for DeepSeek-V3.1 (1.7× as much) and $1.00 for Kimi K2 Instruct (3.8× as much).

Which scores higher on benchmarks?

Kimi K2 Instruct scores higher on the Capabilities Index (ECI): Kimi K2 Instruct 139.9 (#112 of 165), DeepSeek-V3.1 139.8 (#113 of 165) and GPT OSS 120B 139.8 (#114 of 165). The confidence ranges of the top two overlap (136.3–141.6 vs 135.6–143.2), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-V3.1, GPT OSS 120B and Kimi K2 Instruct yet, so there is no like-for-like coding score. On overall capability, Kimi K2 Instruct 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?

DeepSeek-V3.1, GPT OSS 120B and Kimi K2 Instruct share the same 131,072-token context window. Maximum output per response: DeepSeek-V3.1 up to 8,192, GPT OSS 120B up to 32,768, Kimi K2 Instruct up to 32,768 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-V3.1 accepts text; GPT OSS 120B accepts text; Kimi K2 Instruct accepts text. They handle the same number of input types.

Are any of these open source?

Yes, all three publish their weights (MIT License and Modified MIT), so you can self-host them.

Which is newer?

DeepSeek-V3.1 is the newest, released Aug 21, 2025. GPT OSS 120B came out Aug 5, 2025; Kimi K2 Instruct came out Jul 11, 2025. Knowledge cutoff: GPT OSS 120B Jun 2024.

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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