Beam 1.0 vs Kimi K3
Kimi K3 leads the LLM Stats Score 51.9 to 44.6. Beam 1.0 is 9.5x cheaper per token.
Reflection AI · Moonshot AI · Updated for 2026
Which is better?
Kimi K3 leads the overall LLM Stats Score 51.9 to 44.6, ranking #14 overall.
In the 8 individual benchmarks reported for both models, Kimi K3 wins 7; this is a narrower head-to-head signal than the composite indexes.
On price, Beam 1.0 is roughly 9.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Beam 1.0
- cost matters — it's about 9.5x cheaper per token
- you want the most recent training data — it shipped Oct 2026
Choose Kimi K3
- overall performance matters — it scores 51.9 and ranks #14 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 7 of 8 exact shared results
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
22 reported for Beam 1.0 · 31 for Kimi K3
Beam 1.0 outperforms in 1 benchmarks (AutomationBench), while Kimi K3 is better at 7 benchmarks (BrowseComp, DeepSearchQA, DeepSWE 1.1, GPQA, Humanity's Last Exam, MCP Atlas, Terminal-Bench 2.1).
Kimi K3 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, Beam 1.0 ($0.40/1M tokens) is 7.1x cheaper than Kimi K3 ($2.85/1M tokens).
For output processing, Beam 1.0 ($1.20/1M tokens) is 11.9x cheaper than Kimi K3 ($14.25/1M tokens).
In conclusion, Kimi K3 is more expensive than Beam 1.0.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K3 has 2298.7B more parameters than Beam 1.0, making it 458.5% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Kimi K3 can generate longer responses up to 1,048,576 tokens, while Beam 1.0 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Kimi K3 supports multimodal inputs, whereas Beam 1.0 does not.
Kimi K3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Beam 1.0
Kimi K3
License
Usage and distribution terms
Beam 1.0 is licensed under Apache 2.0, while Kimi K3 uses Kimi K3 License.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Kimi K3 License
Open weights
Release Timeline
When each model was launched
Beam 1.0 was released on 2026-10-16, while Kimi K3 was released on 2026-07-16.
Beam 1.0 is 3 months newer than Kimi K3.
Oct 16, 2026
3 days ago
3mo newerJul 16, 2026
3 months ago
Knowledge Cutoff
When training data ends
Beam 1.0 has a documented knowledge cutoff of 2026-06-30, while Kimi K3's cutoff date is not specified.
We can confirm Beam 1.0's training data extends to 2026-06-30, but cannot make a direct comparison without Kimi K3's cutoff date.
Jun 2026
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Provider Availability
Beam 1.0 is available from Together, Reflection AI. Kimi K3 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
Beam 1.0
Kimi K3
Outputs Comparison
Judge for yourself.
Run your own prompts against Beam 1.0 and Kimi K3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Beam 1.0 vs Kimi K3.