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Kimi K2.7 Code vs Llama 3.3 70B Instruct

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Kimi K2.7 Code and Llama 3.3 70B Instruct.

Moonshot AI

Kimi K2.7 Code

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts...

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Meta

Llama 3.3 70B Instruct

Meta's state-of-the-art open weights model, providing enterprise-grade reasoning and logic. Exceptionally powerful for self-hosted customer support, text generation, and tooling workflows.

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Technical Specifications

SpecificationKimi K2.7 CodeLlama 3.3 70B Instruct
ProviderMoonshot AIMeta
Context Window262,144 tokens131,072 tokens
Agent SuitabilityN/A83/100
Time to First Token (TTFT)N/A280 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-06-122024-12-06

API Pricing Comparison

Input Price per Million Tokens

Kimi K2.7 Code

$0.74

Llama 3.3 70B Instruct

$0.10

Output Price per Million Tokens

Kimi K2.7 Code

$3.50

Llama 3.3 70B Instruct

$0.32

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8500.0%vs8620.0%
Kimi K2.7 Code
Llama 3.3 70B Instruct
HumanEvalPython coding & logic synthesis
9320.0%vs8800.0%
Kimi K2.7 Code
Llama 3.3 70B Instruct
MATHComplex mathematical problem solving
7650.0%vs7500.0%
Kimi K2.7 Code
Llama 3.3 70B Instruct
GPQAGraduate-level expert reasoning
4600.0%vs5200.0%
Kimi K2.7 Code
Llama 3.3 70B Instruct
HellaSwagCommonsense reasoning and inference
8600.0%vs8850.0%
Kimi K2.7 Code
Llama 3.3 70B Instruct
MT-BenchMulti-turn conversation flow quality
900.0%vs880.0%
Kimi K2.7 Code
Llama 3.3 70B Instruct

Kimi K2.7 Code Quirks & Gotchas

No developer gotchas reported.

Llama 3.3 70B Instruct Quirks & Gotchas

  • โ–ธStable, well-documented self-hosted option with strong community support
  • โ–ธOutperformed by Llama 4 Maverick for agentic tool-calling workflows