DeepSeek Coder V2 vs Groq Llama 3.3 70B

Performance benchmarks + pricing comparison — updated April 2026

DeepSeek Coder V2

DeepSeek

DeepSeek's coding-specialized model. Open-source and very affordable.

Input	$0.270/M
Output	$1.10/M
Context	128K tokens
Best For	Code generation, code review, debugging
Benchmark	58/100

Groq

Llama 3.3 70B running on Groq's ultra-fast LPU inference. Sub-100ms responses for 70B model.

Input	$0.590/M
Output	$0.790/M
Context	128K tokens
Best For	Real-time applications, fast chat, low-latency coding

Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.

Scenario	DeepSeek Coder V2	Groq Llama 3.3 70B	Savings
Small Script (1K lines)	$0.04	$0.04	DeepSeek Coder V2 saves <$0.01 (4%)
Medium Feature (10K lines)	$0.31	$0.36	DeepSeek Coder V2 saves $0.05 (14%)
Large Project (50K lines)	$1.57	$1.82	DeepSeek Coder V2 saves $0.25 (14%)
Code Review (5K lines)	$0.07	$0.12	DeepSeek Coder V2 saves $0.05 (39%)

DeepSeek Coder V2 wins on both price and performance — $0.270/M input with a benchmark score of N/A/100.

For most developers, this is the clear choice between these two models.

Anthropic's balanced model for coding and general tasks. Best price-performance ratio in the Claude family.

Anthropic's most powerful model. Best for complex reasoning and challenging coding tasks.

Previous generation Sonnet. Still excellent for coding tasks at the same price point.

Fast, cost-effective model for high-volume tasks. Great for code review and simple queries.

First generation Opus. Highest reasoning capability in the Claude 3 family.

First generation Sonnet. Balanced performance for general tasks.