Llama 4 Maverick is Meta's best open-weight model — free, self-hostable, and surprisingly capable. Claude Sonnet 4.6 is the premium daily driver for developers and knowledge workers. Claude leads on every capability benchmark: coding (79.6% SWE-bench vs Llama's ~50%), writing quality, and long-context work with a 1M token window vs Llama's 256K. Llama wins on cost (free or ~$0.20/1M via inference providers), data sovereignty (self-host with no external API calls), and flexibility to fine-tune. If your budget allows, Claude is significantly more capable. If cost or data control is non-negotiable, Llama 4 Maverick is the best free alternative.
MetaBudget
Llama 4 Maverick
Best flexible option for teams that need open-weight portability.
VS
AnthropicPremium
Claude Sonnet 4.6
Best daily driver for coding and writing — the model most developers actually reach for.
Winner
At a glance
Llama 4 Maverick
Claude Sonnet 4.6
Input cost / 1M tokens
$$0.60/1M
$$3.00/1M
Output cost / 1M tokens
$$1.60/1M
$$15.00/1M
Context window
256k tokens
1M tokens
Speed
Fast
Balanced
Price tier
Budget
Premium
Benchmarks
SWE-bench (coding)
32%
79.6%
Arena Elo
1,250
1,340
MMLU
85.5%
88.3%
How they compare
Which model wins for each use case — and why.
CodingClaude Sonnet 4.6 wins
Claude Sonnet 4.6 scores 79.6% on SWE-bench — significantly ahead of Llama 4 Maverick's ~50%. For production coding, Claude is substantially stronger.
WritingClaude Sonnet 4.6 wins
Claude Sonnet 4.6 consistently produces cleaner, more natural prose. Llama 4 Maverick is capable but can be verbose and less tonally precise.
CostLlama 4 Maverick wins
Llama 4 Maverick is free to self-host or costs ~$0.20/1M via inference providers. Claude Sonnet 4.6 costs $3/1M. At high volume, Llama is dramatically cheaper.
Data PrivacyLlama 4 Maverick wins
Llama 4 Maverick can be self-hosted — no data leaves your infrastructure. Critical for regulated industries, sensitive workloads, or GDPR compliance.
Context WindowClaude Sonnet 4.6 wins
Claude Sonnet 4.6 supports 1M tokens vs Llama 4 Maverick's 256K — 4× larger. For long-document analysis, Claude wins decisively.
Which should you pick?
Pick Llama 4 Maverick if…
API costs are prohibitive and you need a free or near-free capable model
Data sovereignty is required — you cannot send data to external APIs
You want to fine-tune a model on your own domain data
You're comfortable with self-hosting or using inference providers like Groq or Together AI
For most workflows, Claude Sonnet 4.6 is the stronger choice.
The best all-around model for most developers and writers. Strong SWE-bench, excellent writing, 1M context — all at $3/1M input. Hard to beat as a daily driver.
The case for each model
What each one is genuinely good at, where it falls down, and when we would steer you away from it.
Our overall pick in this comparison. Against Llama 4 Maverick it costs about 88% more per token and takes 4x the context.
The default model powering Cursor and Windsurf. 79.6% SWE-bench, 1M context window, and best-in-tier writing quality — all at $3/1M input.
Input
$3.00/1M
Output
$15.00/1M
Context
1M tokens
Speed
Balanced
What people actually use it for
Daily coding in Cursor — debugging, refactoring, and feature implementation
Drafting polished client reports, strategy memos, and long-form editorial content
Answering research questions with up to 1M tokens of document context
Where it wins
Strong coding quality with 1M context at $3/1M input
Default model in Cursor and Windsurf, the two most popular AI coding editors
Best writing quality in its price tier — tone, long-form clarity, editorial polish
Where it falls down
Claude Opus 4.7 has a higher current premium coding ceiling
GPT-5.5 or GPT-5.4 are better picks when OpenAI computer-use workflows are the priority
Skip it if
You specifically need desktop-control capabilities (GPT-5.5/GPT-5.4) or the absolute highest coding ceiling (Opus 4.7).
Our verdict
The best all-around model for most developers and writers. Strong SWE-bench, excellent writing, 1M context — all at $3/1M input. Hard to beat as a daily driver.
Llama 4 Maverick is capable but significantly trails Claude Sonnet 4.6 on coding (50% vs 79.6% SWE-bench), writing quality, and context window size. The gap has narrowed from earlier generations but Claude remains substantially stronger.
Is Llama 4 free?
Llama 4 is open-weight (Meta license) and free to self-host. Hosted inference via Groq, Together AI, or Fireworks starts at around $0.20/1M input tokens. Claude Sonnet 4.6 costs $3/1M.
When should I use Llama instead of Claude?
Use Llama 4 when: (1) API costs are prohibitive at your volume, (2) you need on-premise deployment for data sovereignty, or (3) you want to fine-tune on your own data. For maximum output quality, Claude is the stronger choice.