Model Comparison

Kimi K2 Instruct vs Llama 3.1 8B Instruct

Kimi K2 Instruct significantly outperforms across most benchmarks. Llama 3.1 8B Instruct is 16.7x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

Kimi K2 Instruct outperforms in 5 benchmarks (GPQA, HumanEval, IFEval, MMLU, MMLU-Pro), while Llama 3.1 8B Instruct is better at 0 benchmarks.

Kimi K2 Instruct significantly outperforms across most benchmarks.

Sun May 10 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.1 8B Instruct costs less

For input processing, Kimi K2 Instruct ($0.50/1M tokens) is 16.7x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

For output processing, Kimi K2 Instruct ($0.50/1M tokens) is 16.7x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

In conclusion, Kimi K2 Instruct is more expensive than Llama 3.1 8B Instruct.*

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

Lowest available price from all providers

Sun May 10 2026 • llm-stats.com

Kimi K2 Instruct

Input tokens$0.50

Output tokens$0.50

Best providerFireworks

Llama 3.1 8B Instruct

Input tokens$0.03

Output tokens$0.03

Best providerLambda

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

992.0B diff

Kimi K2 Instruct has 992.0B more parameters than Llama 3.1 8B Instruct, making it 12400.0% larger.

Kimi K2 Instruct

1.0Tparameters

Llama 3.1 8B Instruct

8.0Bparameters

1000.0B

Kimi K2 Instruct

8.0B

Llama 3.1 8B Instruct

Context Window

Maximum input and output token capacity

Kimi K2 Instruct accepts 200,000 input tokens compared to Llama 3.1 8B Instruct's 131,072 tokens. Kimi K2 Instruct can generate longer responses up to 200,000 tokens, while Llama 3.1 8B Instruct is limited to 131,072 tokens.

Kimi K2 Instruct

Input200,000 tokens

Output200,000 tokens

Llama 3.1 8B Instruct

Input131,072 tokens

Output131,072 tokens

Sun May 10 2026 • llm-stats.com

License

Usage and distribution terms

Kimi K2 Instruct is licensed under MIT, while Llama 3.1 8B Instruct uses Llama 3.1 Community License.

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

Kimi K2 Instruct

MIT

Open weights

Llama 3.1 8B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

Kimi K2 Instruct was released on 2025-07-11, while Llama 3.1 8B Instruct was released on 2024-07-23.

Kimi K2 Instruct is 12 months newer than Llama 3.1 8B Instruct.

Kimi K2 Instruct

Jul 11, 2025

10 months ago

11mo newer

Llama 3.1 8B Instruct

Jul 23, 2024

1.8 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 8B Instruct has a documented knowledge cutoff of 2023-12-31, while Kimi K2 Instruct's cutoff date is not specified.

We can confirm Llama 3.1 8B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without Kimi K2 Instruct's cutoff date.

Kimi K2 Instruct

—

Llama 3.1 8B Instruct

Dec 2023

Provider Availability

Kimi K2 Instruct is available from Fireworks, Novita. Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock.

Kimi K2 Instruct

Fireworks

Input Price:Input: $0.50/1MOutput Price:Output: $0.50/1M

Novita

Input Price:Input: $0.57/1MOutput Price:Output: $2.30/1M

Llama 3.1 8B Instruct

Lambda

Input Price:Input: $0.03/1MOutput Price:Output: $0.03/1M

Deepinfra

Input Price:Input: $0.05/1MOutput Price:Output: $0.05/1M

Groq

Input Price:Input: $0.05/1MOutput Price:Output: $0.08/1M

Sambanova

Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M

Cerebras

Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M

Hyperbolic

Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M

Together

Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M

Fireworks

Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M

AWS Bedrock

Input Price:Input: $0.22/1MOutput Price:Output: $0.22/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Kimi K2 Instruct

View details

Moonshot AI

Larger context window (200,000 tokens)

Higher GPQA score (75.1% vs 30.4%)

Higher HumanEval score (93.3% vs 72.6%)

Higher IFEval score (89.8% vs 80.4%)

Higher MMLU score (89.5% vs 69.4%)

Higher MMLU-Pro score (81.1% vs 48.3%)

Llama 3.1 8B Instruct

View details

Detailed Comparison

AI Model Comparison Table
Feature	Kimi K2 Instruct	Llama 3.1 8B Instruct

FAQ

Common questions about Kimi K2 Instruct vs Llama 3.1 8B Instruct.

Which is better, Kimi K2 Instruct or Llama 3.1 8B Instruct?

Kimi K2 Instruct significantly outperforms across most benchmarks. Kimi K2 Instruct is made by Moonshot AI and Llama 3.1 8B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Kimi K2 Instruct compare to Llama 3.1 8B Instruct in benchmarks?

Kimi K2 Instruct scores MATH-500: 97.4%, GSM8k: 97.3%, CBNSL: 95.6%, HumanEval: 93.3%, MMLU-Redux: 92.7%. Llama 3.1 8B Instruct scores GSM-8K (CoT): 84.5%, ARC-C: 83.4%, API-Bank: 82.6%, IFEval: 80.4%, BFCL: 76.1%.

Is Kimi K2 Instruct cheaper than Llama 3.1 8B Instruct?

Llama 3.1 8B Instruct is 16.7x cheaper for input tokens. Kimi K2 Instruct costs $0.50/M input and $0.50/M output via fireworks. Llama 3.1 8B Instruct costs $0.03/M input and $0.03/M output via lambda.

What are the context window sizes for Kimi K2 Instruct and Llama 3.1 8B Instruct?

Kimi K2 Instruct supports 200K tokens and Llama 3.1 8B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Kimi K2 Instruct and Llama 3.1 8B Instruct?

Key differences include context window (200K vs 131K), input pricing ($0.50 vs $0.03/M), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi K2 Instruct and Llama 3.1 8B Instruct?

Kimi K2 Instruct is developed by Moonshot AI and Llama 3.1 8B Instruct is developed by Meta.