Claude Sonnet 4.6 vs Llama 4 Maverick
| Signal | Claude Sonnet 4.6 | Delta | Llama 4 Maverick |
|---|---|---|---|
Capabilities | 100 | +33 | |
Benchmarks | 82 | +7 | |
Pricing | 85 | -14 | |
Context window size | 95 | +4 | |
Recency | 87 | +58 | |
Output Capacity | 82 | +14 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
85.2
current score
Claude Sonnet 4.6
right now
70.4
current score
Claude Sonnet 4.6
Anthropic
Llama 4 Maverick
Meta
Llama 4 Maverick saves you $998.63/month
That's $11983.50/year compared to Claude Sonnet 4.6 at your current usage level of 100K calls/month.
| Metric | Claude Sonnet 4.6 | Llama 4 Maverick | Winner |
|---|---|---|---|
| Overall Score | 85 | 70 | Claude Sonnet 4.6 |
| Rank | #63 | #118 | Claude Sonnet 4.6 |
| Quality Rank | #63 | #118 | Claude Sonnet 4.6 |
| Adoption Rank | #63 | #118 | Claude Sonnet 4.6 |
| Parameters | -- | -- | -- |
| Context Window | 1000K | 524K | Claude Sonnet 4.6 |
| Pricing | $3.00/$15.00/M | $0.19/$0.65/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 67 | Claude Sonnet 4.6 |
| Benchmarks | 82 | 76 | Claude Sonnet 4.6 |
| Pricing | 85 | 99 | Llama 4 Maverick |
| Context window size | 95 | 91 | Claude Sonnet 4.6 |
| Recency | 87 | 29 | Claude Sonnet 4.6 |
| Output Capacity | 82 | 67 | Claude Sonnet 4.6 |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 85/100 (rank #63), placing it in the top 79% of all 290 models tracked.
Scores 70/100 (rank #118), placing it in the top 60% of all 290 models tracked.
Claude Sonnet 4.6 has a 15-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Choose Claude Sonnet 4.6 when you need:
- Processing long documents or large codebases (1000K token context)
- Step-by-step reasoning and chain-of-thought problem solving
Choose Llama 4 Maverick when you need:
- High-volume production workloads where API costs must be minimized
- Self-hosted deployments where you need full control over the model
Llama 4 Maverick offers 95% better value per quality point. At 1M tokens/day, you'd spend $12.60/month with Llama 4 Maverick vs $270.00/month with Claude Sonnet 4.6 - a $257.40 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Llama 4 Maverick also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.65/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (85/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Claude Sonnet 4.6 clearly outperforms Llama 4 Maverick with a significant 14.799999999999997-point lead. For most general use cases, Claude Sonnet 4.6 is the stronger choice. However, Llama 4 Maverick may still excel in niche scenarios.
By Use Case
Best for Quality
Claude Sonnet 4.6
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 4 Maverick
95% lower pricing; better value at scale
Best for Reliability
Claude Sonnet 4.6
Higher uptime and faster response speeds
Best for Prototyping
Claude Sonnet 4.6
Stronger community support and better developer experience
Best for Production
Claude Sonnet 4.6
Wider enterprise adoption and proven at scale
by Anthropic
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Reliability - Higher uptime and faster response speeds
- Choose for Prototyping - Stronger community support and better developer experience
- Choose for Production - Wider enterprise adoption and proven at scale
| Capability | Claude Sonnet 4.6 | Llama 4 Maverick |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
Claude Sonnet 4.6
Anthropic
Llama 4 Maverick
Meta
Llama 4 Maverick saves you $22.28/month
That's 95% cheaper than Claude Sonnet 4.6 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Claude Sonnet 4.6 | Llama 4 Maverick |
|---|---|---|
| Context Window | 1M | 524K |
| Max Output Tokens | 128,000 | 16,384 |
| Open Source | No | Yes |
| Created | Feb 17, 2026 | Apr 5, 2025 |
The $15/M output pricing reflects Claude's 66/100 performance placing it in the top 2% of coding models (#6 of 326), while Llama 4 Maverick's 54/100 score puts it in the top 18% (#59). Beyond raw performance, Claude includes reasoning and web search capabilities that Llama lacks, making it suitable for autonomous coding agents that need to research documentation and explain their logic.
Daily costs would be $54 for Claude Sonnet 4.6 (8M × $3/M + 2M × $15/M) versus $3.60 for Llama 4 Maverick (8M × $0.15/M + 2M × $0.6/M). The 15x daily cost difference ($18,810/year vs $1,314/year) makes Llama compelling for high-volume applications where the 12-point performance gap is acceptable.
Claude's 8x larger output capacity (128K vs 16K) enables generating entire codebases or comprehensive refactoring reports in a single response, critical for the 66/100 performance tier. Llama's 16K output forces multi-turn interactions for large code generation tasks, partially explaining the 53-position rank gap despite identical input context.
Claude's reasoning capability and 66/100 score make it optimal for complex debugging and architecture design where explaining the "why" matters as much as the code itself. The open-source advantage of Llama (allowing fine-tuning and on-premise deployment) becomes less relevant when you need Claude's web search to automatically fetch latest API documentation during code generation.
Without reasoning, Llama cannot explain its coding decisions or debug its own outputs, limiting it to straightforward code completion despite the respectable 54/100 score. The missing web search means developers must manually provide all context, while Claude at $15/M output can autonomously fetch Stack Overflow solutions and documentation, partially justifying the 25x price premium for complex projects.