GPT OSS 120B vs Kimi K2-Thinking-0905
Kimi K2-Thinking-0905 leads the LLM Stats Score 36.0 to 28.8. GPT OSS 120B is 12.1x cheaper per token.
OpenAI · Moonshot AI · Updated for 2026
Which is better?
Kimi K2-Thinking-0905 leads the overall LLM Stats Score 36.0 to 28.8, ranking #80 overall.
In the 3 individual benchmarks reported for both models, Kimi K2-Thinking-0905 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, GPT OSS 120B is roughly 12.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K2-Thinking-0905 also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT OSS 120B
- cost matters — it's about 12.1x cheaper per token
Choose Kimi K2-Thinking-0905
- overall performance matters — it scores 36.0 and ranks #80 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
7 reported for GPT OSS 120B · 21 for Kimi K2-Thinking-0905
GPT OSS 120B outperforms in 0 benchmarks, while Kimi K2-Thinking-0905 is better at 3 benchmarks (GPQA, HealthBench, Humanity's Last Exam).
Kimi K2-Thinking-0905 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT OSS 120B ($0.04/1M tokens) is 12.7x cheaper than Kimi K2-Thinking-0905 ($0.47/1M tokens).
For output processing, GPT OSS 120B ($0.17/1M tokens) is 11.8x cheaper than Kimi K2-Thinking-0905 ($2.00/1M tokens).
In conclusion, Kimi K2-Thinking-0905 is more expensive than GPT OSS 120B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2-Thinking-0905 has 883.2B more parameters than GPT OSS 120B, making it 756.2% larger.
Context Window
Maximum input and output token capacity
Kimi K2-Thinking-0905 accepts 262,144 input tokens compared to GPT OSS 120B's 131,072 tokens. Kimi K2-Thinking-0905 can generate longer responses up to 262,144 tokens, while GPT OSS 120B is limited to 131,072 tokens.
License
Usage and distribution terms
GPT OSS 120B is licensed under Apache 2.0, while Kimi K2-Thinking-0905 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
GPT OSS 120B was released on 2025-08-05, while Kimi K2-Thinking-0905 was released on 2025-09-05.
Kimi K2-Thinking-0905 is 1 month newer than GPT OSS 120B.
Aug 5, 2025
1.1 years ago
Sep 5, 2025
1.0 years ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT OSS 120B is available from DeepInfra, Novita, OpenAI, Fireworks, Groq. Kimi K2-Thinking-0905 is available from DeepInfra, Novita, Fireworks.
GPT OSS 120B
Kimi K2-Thinking-0905
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT OSS 120B and Kimi K2-Thinking-0905 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT OSS 120B vs Kimi K2-Thinking-0905.