← Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Claude Opus 4.6 vs Llama 4 Maverick

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 Claude Opus 4.6 and Llama 4 Maverick.

Anthropic

Claude Opus 4.6

Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective...

View Full Specs
Meta

Llama 4 Maverick

Meta's next-generation open weights model. Delivers premium agentic capabilities, reasoning, and tool call compliance for local or self-hosted enterprise stacks.

View Full Specs

Technical Specifications

SpecificationClaude Opus 4.6Llama 4 Maverick
ProviderAnthropicMeta
Context Window1,000,000 tokens1,048,576 tokens
Agent Suitability95/10089/100
Time to First Token (TTFT)500 ms300 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-02-042026-05-25

API Pricing Comparison

Input Price per Million Tokens

Claude Opus 4.6

$5.00

Llama 4 Maverick

$0.15

Output Price per Million Tokens

Claude Opus 4.6

$25.00

Llama 4 Maverick

$0.60

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
9250.0%vs9150.0%
Claude Opus 4.6
Llama 4 Maverick
HumanEvalPython coding & logic synthesis
9450.0%vs9380.0%
Claude Opus 4.6
Llama 4 Maverick
MATHComplex mathematical problem solving
8890.0%vs8920.0%
Claude Opus 4.6
Llama 4 Maverick
GPQAGraduate-level expert reasoning
7980.0%vs7640.0%
Claude Opus 4.6
Llama 4 Maverick
HellaSwagCommonsense reasoning and inference
9750.0%vs9720.0%
Claude Opus 4.6
Llama 4 Maverick
MT-BenchMulti-turn conversation flow quality
965.0%vs940.0%
Claude Opus 4.6
Llama 4 Maverick

Claude Opus 4.6 Quirks & Gotchas

  • Best for long-context document analysis and legal review
  • Tool calling requires structured prompt — prone to verbose refusal without explicit output schema

Llama 4 Maverick Quirks & Gotchas

  • Self-hostable via Ollama/Docker — ideal for on-premise deployments
  • Requires specific system prompt for optimal function calling reliability