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Comparison · 3 models · Updated Nov 2, 2026

Gemini 2.5 Flash vs GPT OSS 120B vs Kimi K2 Instruct

Gemini 2.5 Flash comes out ahead, 66 to 58 and 50 on our weighted score, though GPT OSS 120B is 3.2× cheaper per token.

  1. Our pick

    Google

    Gemini 2.5 Flash

    Released Jun 17, 2025

    66/100
    • ECI140.6
    • Price$0.30 / $2.50
    • Context1.05M
    Full specs Remove Gemini 2.5 Flash

  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

Gemini 2.5 Flash is our pick

Gemini 2.5 Flash is the better all-round choice, scoring 66/100 against GPT OSS 120B (58) and Kimi K2 Instruct (50). It leads on inputs & features and context window. GPT OSS 120B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGemini 2.5 FlashCapabilities Index (ECI): Gemini 2.5 Flash 140.6 · Kimi K2 Instruct 139.9 · GPT OSS 120B 139.8
  • Lowest priceGPT OSS 120BGPT OSS 120B $0.263 · Gemini 2.5 Flash $0.85 · Kimi K2 Instruct $1.00 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 FlashGemini 2.5 Flash 1,048,576 · GPT OSS 120B 131,072 · Kimi K2 Instruct 131,072 tokens
  • Widest inputsGemini 2.5 FlashGemini 2.5 Flash: Text, Images, PDFs, Audio, Video · GPT OSS 120B: Text · Kimi K2 Instruct: Text
  • Self-hostingGPT OSS 120B and Kimi K2 InstructPublishes downloadable weights (Modified MIT)
How the score is built
MeasureWeightGemini 2.5 FlashGPT OSS 120BKimi K2 Instruct
CapabilityCapabilities Index (ECI)50%656464
Price25%517448
Inputs & features15%1003525
Context window10%612525
Overall100%66/10058/10050/100
02 — Side by side

Every spec in one table

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

Gemini 2.5 Flash vs GPT OSS 120B vs Kimi K2 Instruct specifications side by side
SpecificationGemini 2.5 FlashGoogleGPT OSS 120BOpenAIKimi K2 InstructMoonshot AI
Capability
Capabilities Index (ECI)140.6 (best)139.8139.9
ECI rank#110 of 165 (best)#114 of 165#112 of 165
GPQA DiamondGraduate-level science questions—75.8%—
OTIS Mock AIME 2024–2025Competition mathematics—88.9%—
Price per million tokens
Input$0.30$0.15 (best)$0.57
Output$2.50$0.60 (best)$2.30
Cached input$0.03——
Blended (3:1)$0.85$0.263 (best)$1.00
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Google APIMedian of 65 providersMedian of 11 providers
Limits
Context window1,048,576 tokens (best)131,072 tokens131,072 tokens
Max output65,536 tokens (best)32,768 tokens32,768 tokens
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsYesNoNo
AudioYesNoNo
VideoYesNoNo
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsProprietaryOpenOpenModified MIT
API model IDgemini-2.5-flash——
API providers3267 (best)11
ReleasedJun 17, 2025Aug 5, 2025Jul 11, 2025
Knowledge cutoffJan 2025Jun 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.

  • Gemini 2.5 Flash$8.00
  • GPT OSS 120B$2.70
  • Kimi K2 Instruct$10.30
04 — Questions

Which should you choose?

Which is better: Gemini 2.5 Flash, GPT OSS 120B or Kimi K2 Instruct?

Gemini 2.5 Flash is the better all-round choice, scoring 66/100 against GPT OSS 120B (58) and Kimi K2 Instruct (50). It leads on inputs & features and context window. GPT OSS 120B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemini 2.5 Flash, 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). Gemini 2.5 Flash costs $0.30 input / $2.50 output per million tokens (official Google API price); 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 $0.85 for Gemini 2.5 Flash (3.2× as much) and $1.00 for Kimi K2 Instruct (3.8× as much).

Which scores higher on benchmarks?

Gemini 2.5 Flash scores higher on the Capabilities Index (ECI): Gemini 2.5 Flash 140.6 (#110 of 165), Kimi K2 Instruct 139.9 (#112 of 165) and GPT OSS 120B 139.8 (#114 of 165). The confidence ranges of the top two overlap (138.4–142.1 vs 136.3–141.6), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for Gemini 2.5 Flash, GPT OSS 120B and Kimi K2 Instruct yet, so there is no like-for-like coding score. On overall capability, Gemini 2.5 Flash 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?

Gemini 2.5 Flash has the largest context window at 1,048,576 tokens, against 131,072 for GPT OSS 120B and 131,072 for Kimi K2 Instruct. Maximum output per response: Gemini 2.5 Flash up to 65,536, GPT OSS 120B up to 32,768, Kimi K2 Instruct up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Gemini 2.5 Flash accepts text, images, PDFs, audio and video; GPT OSS 120B accepts text; Kimi K2 Instruct accepts text. Gemini 2.5 Flash handles the widest range of inputs.

Are any of these open source?

GPT OSS 120B and Kimi K2 Instruct publishes its weights (Modified MIT) and can be self-hosted; Gemini 2.5 Flash is proprietary.

Which is newer?

GPT OSS 120B is the newest, released Aug 5, 2025. Kimi K2 Instruct came out Jul 11, 2025; Gemini 2.5 Flash came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash Jan 2025, 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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