Claude Sonnet 4.5 vs Llama 3.1 405B Instruct
At a Glance
| Compare | Claude Sonnet 4.5Anthropic | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #36 of 4627.7 score · 2/3 sources · provisional · missing LiveBench · full-core range 18.5–51.8 | UnrankedNot in the 46-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $3.00Anthropic ↗ · Sep 3, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $15.00Anthropic ↗ · Sep 3, 2026 | Not reported |
| Context windowMaximum documented tokens | 200K | 131K |
| Model facts checked | Sep 3, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Claude Sonnet 4.5 | Llama-3.1-405B-Instruct |
|---|---|---|
| Developer | Anthropic | Meta |
| Family | Claude 4 | Llama 3 1 405b Instruct |
| Model | Claude Sonnet 4.5 | Llama-3.1-405B-Instruct |
| Version | Claude Sonnet 4.5 | Llama-3.1-405B-Instruct |
| Lifecycle | active | active |
| Released | 2025-09-29 | 2024-07-23 |
| Knowledge cutoff | 2025-01-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 200K | 131K |
| Total parameters | Unknown | 405.9B |
| Active parameters | Unknown | Unknown |
| License | Unknown | llama3.1 |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard) | Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, tools |
Claude Sonnet 4.5 Capabilities
Llama 3.1 405B Instruct Capabilities
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Primary Evidence
Sources and Freshness
Questions
Claude Sonnet 4.5 vs Llama 3.1 405B Instruct FAQs
Is Claude Sonnet 4.5 or Llama 3.1 405B Instruct better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Sonnet 4.5 and Llama 3.1 405B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Sonnet 4.5 or Llama 3.1 405B Instruct?+
Only Claude Sonnet 4.5 has a directly sourced input price: $3.00 per million tokens. Only Claude Sonnet 4.5 has a directly sourced output price: $15.00 per million tokens.
Which has a larger context window, Claude Sonnet 4.5 or Llama 3.1 405B Instruct?+
Claude Sonnet 4.5 has the larger sourced context window. Claude Sonnet 4.5 supports 200K and Llama 3.1 405B Instruct supports 131K.
Which performs better in benchmarks, Claude Sonnet 4.5 or Llama 3.1 405B Instruct?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Claude Sonnet 4.5 or Llama 3.1 405B Instruct be self-hosted?+
Llama 3.1 405B Instruct is the only model in this pair currently marked as self-hostable. Claude Sonnet 4.5 is not marked open weight; Llama 3.1 405B Instruct is open weight.
Can Claude Sonnet 4.5 and Llama 3.1 405B Instruct understand images?+
Claude Sonnet 4.5 is documented with image input; Llama 3.1 405B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Sonnet 4.5 or Llama 3.1 405B Instruct?+
Neither has a larger sourced maximum output. Claude Sonnet 4.5 is 64K and Llama 3.1 405B Instruct is —.
Do Claude Sonnet 4.5 and Llama 3.1 405B Instruct support reasoning and tool use?+
Claude Sonnet 4.5: reasoning, tool calling, and image input. Llama 3.1 405B Instruct: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Sonnet 4.5 or Llama 3.1 405B Instruct?+
Claude Sonnet 4.5 has 1 sourced provider route; Llama 3.1 405B Instruct has 1, a tie.
Which offers better value, Claude Sonnet 4.5 or Llama 3.1 405B Instruct?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.