Model Comparison

North Mini Code 1.0 vs Kimi K3Which is better in 2026?

Comparing North Mini Code 1.0 and Kimi K3 across benchmarks, pricing, and capabilities.

Verdict: North Mini Code 1.0 vs Kimi K3 — which is better?

North Mini Code 1.0 (by Cohere) and Kimi K3 (by Moonshot AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose North Mini Code 1.0 if…

  • you need open weights you can self-host or fine-tune

Choose Kimi K3 if…

  • you want the most recent training data — it shipped Jul 2026

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

North Mini Code 1.0 and Kimi K3don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

2770.0B diff

Kimi K3 has 2770.0B more parameters than North Mini Code 1.0, making it 9233.3% larger.

Cohere
North Mini Code 1.0
30.0Bparameters
Moonshot AI
Kimi K3
2.8Tparameters
30.0B
North Mini Code 1.0
2800.0B
Kimi K3

Context Window

Maximum input and output token capacity

Only Kimi K3 specifies input context (1,048,576 tokens). Only Kimi K3 specifies output context (1,048,576 tokens).

Cohere
North Mini Code 1.0
Input- tokens
Output- tokens
Moonshot AI
Kimi K3
Input1,048,576 tokens
Output1,048,576 tokens
Fri Jul 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Kimi K3 supports multimodal inputs, whereas North Mini Code 1.0 does not.

Kimi K3 can handle both text and other forms of data like images, making it suitable for multimodal applications.

North Mini Code 1.0

Text
Images
Audio
Video

Kimi K3

Text
Images
Audio
Video

Release Timeline

When each model was launched

North Mini Code 1.0 was released on 2026-06-09, while Kimi K3 was released on 2026-07-16.

Kimi K3 is 1 month newer than North Mini Code 1.0.

North Mini Code 1.0

Jun 9, 2026

1 months ago

Kimi K3

Jul 16, 2026

1 days ago

1mo newer

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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Cohere

No standout differentiators in the data we have for this pair.

Moonshot AI
Larger context window (1,048,576 tokens)
Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against North Mini Code 1.0 and Kimi K3 side-by-side, then vote on the output you prefer.

North Mini Code 1.0
✓ Preferred
Kimi K3
Open in Playground
AI Model Comparison Table
Feature
Cohere
North Mini Code 1.0
Moonshot AI
Kimi K3

FAQ

Common questions about North Mini Code 1.0 vs Kimi K3.

Which is better, North Mini Code 1.0 or Kimi K3?

North Mini Code 1.0 (Cohere) and Kimi K3 (Moonshot AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does North Mini Code 1.0 compare to Kimi K3 in benchmarks?

North Mini Code 1.0 scores LiveCodeBench v6: 70.3%, SWE-Bench Verified: 67.6%, SWE-Bench Pro: 40.2%, SciCode: 38.2%, Terminal-Bench 2.0: 36.0%. Kimi K3 scores MathVision: 97.8%, DeepSearchQA: 95.0%, GPQA: 93.5%, CharXiv-R: 91.3%, BrowseComp: 91.2%.

What are the context window sizes for North Mini Code 1.0 and Kimi K3?

North Mini Code 1.0 supports an unknown number of tokens and Kimi K3 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between North Mini Code 1.0 and Kimi K3?

Key differences include multimodal support (no vs yes), licensing (Apache 2.0 vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes North Mini Code 1.0 and Kimi K3?

North Mini Code 1.0 is developed by Cohere and Kimi K3 is developed by Moonshot AI.

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