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Gemini 4 Argon vs Kimi K2.7 Code

Gemini 4 Argon leads the LLM Stats Score 55.1 to 38.7. Kimi K2.7 Code is 2.9x cheaper per token.

Google · Moonshot AI · Updated for 2026

Which is better?

Gemini 4 Argon leads the overall LLM Stats Score 55.1 to 38.7, ranking #4 overall.

In the 1 individual benchmarks reported for both models, Gemini 4 Argon wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, Kimi K2.7 Code is roughly 2.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 4 Argon also accepts a larger context window (1,048,576 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 Gemini 4 Argon

  • overall performance matters — it scores 55.1 and ranks #4 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Sep 2026

Choose Kimi K2.7 Code

  • cost matters — it's about 2.9x cheaper per token
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Gemini 4 Argon
Google
Kimi K2.7 Code
Moonshot AI
Core performance indexes
LLM Stats Score
55.1
#4
38.7
#79
Reasoning
53.2
#6
33.8
#112
Coding
42.5
#7
28.7
#70
Agents
41.2
#4
25.9
#66
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$2.00 / M
$0.68 / M
Output price
$10.00 / M
$3.40 / M
Context window
1,048,576
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Gemini 4 Argon
Kimi K2.7 Code
Tool use
32.3#4
23.0#50
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for Gemini 4 Argon · 9 for Kimi K2.7 Code

1 shared

Gemini 4 Argon outperforms in 1 benchmarks (DeepSWE 1.1), while Kimi K2.7 Code is better at 0 benchmarks.

Gemini 4 Argon significantly outperforms across most benchmarks.

Thu Oct 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Kimi K2.7 Code costs less

For input processing, Gemini 4 Argon ($2.00/1M tokens) is 2.9x more expensive than Kimi K2.7 Code ($0.68/1M tokens).

For output processing, Gemini 4 Argon ($10.00/1M tokens) is 2.9x more expensive than Kimi K2.7 Code ($3.40/1M tokens).

In conclusion, Gemini 4 Argon is more expensive than Kimi K2.7 Code.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Oct 22 2026 • llm-stats.com
Google
Gemini 4 Argon
Input tokens$2.00
Output tokens$10.00
Best providerGoogle
Moonshot AI
Kimi K2.7 Code
Input tokens$0.68
Output tokens$3.40
Best providerDeepinfra
Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

Gemini 4 Argon accepts 1,048,576 input tokens compared to Kimi K2.7 Code's 262,144 tokens. Gemini 4 Argon can generate longer responses up to 1,048,576 tokens, while Kimi K2.7 Code is limited to 262,144 tokens.

Google
Gemini 4 Argon
Input1,048,576 tokens
Output1,048,576 tokens
Moonshot AI
Kimi K2.7 Code
Input262,144 tokens
Output262,144 tokens
Thu Oct 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemini 4 Argon and Kimi K2.7 Code support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemini 4 Argon

Text
Images
Audio
Video

Kimi K2.7 Code

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 4 Argon is licensed under a proprietary license, while Kimi K2.7 Code uses Modified MIT License.

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 4 Argon

Proprietary

Closed source

Kimi K2.7 Code

Modified MIT License

Open weights

Release Timeline

When each model was launched

Gemini 4 Argon was released on 2026-09-30, while Kimi K2.7 Code was released on 2026-06-12.

Gemini 4 Argon is 4 months newer than Kimi K2.7 Code.

Gemini 4 Argon

Sep 30, 2026

2 weeks ago

3mo newer
Kimi K2.7 Code

Jun 12, 2026

4 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Gemini 4 Argon is available from Google. Kimi K2.7 Code is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.

Gemini 4 Argon

google logo
Google
Input Price:Input: $2.00/1MOutput Price:Output: $10.00/1M

Kimi K2.7 Code

deepinfra logo
Deepinfra
Input Price:Input: $0.68/1MOutput Price:Output: $3.40/1M
fireworks logo
Fireworks
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
moonshot logo
Unknown Organization
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
novita logo
Novita
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
together logo
Together
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Gemini 4 Argon and Kimi K2.7 Code side-by-side, then vote on the output you prefer.

Gemini 4 Argon
✓ Preferred
Kimi K2.7 Code
Open in Playground

FAQ

Common questions about Gemini 4 Argon vs Kimi K2.7 Code.

Which is better, Gemini 4 Argon or Kimi K2.7 Code?

Gemini 4 Argon leads the LLM Stats Score 55.1 to 38.7. Gemini 4 Argon is made by Google and Kimi K2.7 Code is made by Moonshot AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 4 Argon compare to Kimi K2.7 Code in benchmarks?

Gemini 4 Argon scores Graphwalks BFS <128k: 99.7%, Vibe Code Bench: 91.9%, LVBench: 91.7%, LABBench2: 88.8%, Graphwalks BFS >128k: 84.2%. Kimi K2.7 Code scores MCP-Mark: 81.1%, MCP Atlas: 76.0%, LiveBench: 71.9%, Kimi Code Bench v2: 62.0%, Program Bench: 53.6%.

Is Gemini 4 Argon cheaper than Kimi K2.7 Code?

Kimi K2.7 Code is 2.9x cheaper for input tokens. Gemini 4 Argon costs $2.00/M input and $10.00/M output via google. Kimi K2.7 Code costs $0.68/M input and $3.40/M output via deepinfra.

What are the context window sizes for Gemini 4 Argon and Kimi K2.7 Code?

Gemini 4 Argon supports 1.0M tokens and Kimi K2.7 Code supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 4 Argon and Kimi K2.7 Code?

Key differences include LLM Stats Score (55.1 vs 38.7), context window (1.0M vs 262K), input pricing ($2.00 vs $0.68/M), licensing (Proprietary vs Modified MIT License). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 4 Argon and Kimi K2.7 Code?

Gemini 4 Argon is developed by Google and Kimi K2.7 Code is developed by Moonshot AI.

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