Kimi K2-Thinking-0905 vs Seed 1.8
Kimi K2-Thinking-0905 and Seed 1.8 are closely matched at 36.0 and 34.2 on the LLM Stats Score. Seed 1.8 is 1.2x cheaper per token.
Moonshot AI · ByteDance · Updated for 2026
Which is better?
Kimi K2-Thinking-0905 and Seed 1.8 are closely matched on the overall LLM Stats Score at 36.0 and 34.2.
In the 7 individual benchmarks reported for both models, Seed 1.8 wins 5; this is a narrower head-to-head signal than the composite indexes.
On price, Seed 1.8 is roughly 1.2x 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 Kimi K2-Thinking-0905
- you process long inputs — it offers a 262,144 token context window
- you need open weights you can self-host or fine-tune
Choose Seed 1.8
- you value its reported benchmark strengths — it wins 5 of 7 exact shared results
- cost matters — it's about 1.2x cheaper per token
- you want the most recent training data — it shipped Feb 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
21 reported for Kimi K2-Thinking-0905 · 57 for Seed 1.8
Kimi K2-Thinking-0905 outperforms in 2 benchmarks (AIME 2025, LiveCodeBench v6), while Seed 1.8 is better at 5 benchmarks (BrowseComp, BrowseComp-zh, MMLU-Pro, Multi-SWE-Bench, SWE-Bench Verified).
Seed 1.8 shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2-Thinking-0905 ($0.47/1M tokens) is 1.9x more expensive than Seed 1.8 ($0.25/1M tokens).
For output processing, Kimi K2-Thinking-0905 ($2.00/1M tokens) costs the same as Seed 1.8 ($2.00/1M tokens).
In conclusion, Kimi K2-Thinking-0905 is more expensive than Seed 1.8.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Kimi K2-Thinking-0905 accepts 262,144 input tokens compared to Seed 1.8's 256,000 tokens. Kimi K2-Thinking-0905 can generate longer responses up to 262,144 tokens, while Seed 1.8 is limited to 256,000 tokens.
Input capabilities
Documented input modalities across available providers
Seed 1.8 supports multimodal inputs, whereas Kimi K2-Thinking-0905 does not.
Seed 1.8 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2-Thinking-0905
Seed 1.8
License
Usage and distribution terms
Kimi K2-Thinking-0905 is licensed under MIT, while Seed 1.8 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Kimi K2-Thinking-0905 was released on 2025-09-05, while Seed 1.8 was released on 2026-02-17.
Seed 1.8 is 6 months newer than Kimi K2-Thinking-0905.
Sep 5, 2025
1.0 years ago
Feb 17, 2026
6 months ago
5mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Kimi K2-Thinking-0905 is available from DeepInfra, Novita, Fireworks. Seed 1.8 is available from DeepInfra.
Kimi K2-Thinking-0905
Seed 1.8
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2-Thinking-0905 and Seed 1.8 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2-Thinking-0905 vs Seed 1.8.