Claude Fable 5.1 vs Llama 3.1 70B
At a Glance
| Compare | Claude Fable 5.1Anthropic |  Llama 3.1 70BMeta |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #1 of 4699.0 score · 3/3 sources · complete | UnrankedNot in the 46-model eligible cohort |
| CostLower is better · Published-token output estimate | #43 of 44$0.824 per LiveBench case | UnrankedNot in the 44-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.5 | #22 of 3851.7 score · 3/3 sources · complete | UnrankedNot in the 38-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $10.00Anthropic ↗ · Sep 3, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $50.00Anthropic ↗ · Sep 3, 2026 | Not reported |
| Context windowMaximum documented tokens | 1,000K | 131K |
| Model facts checked | Sep 2, 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 Fable 5.1 | Llama-3.1-70B |
|---|---|---|
| Developer | Anthropic | Meta |
| Family | Claude 5 1 | Llama 3 1 70b |
| Model | Claude Fable 5.1 | Llama-3.1-70B |
| Version | Claude Fable 5.1 | Llama-3.1-70B |
| Lifecycle | active | active |
| Released | 2026-09-01 | 2024-07-23 |
| Knowledge cutoff | 2026-06-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 131K |
| Total parameters | Unknown | 70.6B |
| Active parameters | Unknown | Unknown |
| License | Unknown | llama3.1 |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard) | Hugging Face (Standard) |
| Capabilities | chat, generation, reasoning, tools | generation |
Claude Fable 5.1 Capabilities
Llama 3.1 70B Capabilities
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Primary Evidence
Sources and Freshness
Questions
Claude Fable 5.1 vs Llama 3.1 70B FAQs
Is Claude Fable 5.1 or Llama 3.1 70B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Fable 5.1 and Llama 3.1 70B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Fable 5.1 or Llama 3.1 70B?+
Only Claude Fable 5.1 has a directly sourced input price: $10.00 per million tokens. Only Claude Fable 5.1 has a directly sourced output price: $50.00 per million tokens.
Which has a larger context window, Claude Fable 5.1 or Llama 3.1 70B?+
Claude Fable 5.1 has the larger sourced context window. Claude Fable 5.1 supports 1,000K and Llama 3.1 70B supports 131K.
Which performs better in benchmarks, Claude Fable 5.1 or Llama 3.1 70B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Claude Fable 5.1 or Llama 3.1 70B be self-hosted?+
Llama 3.1 70B is the only model in this pair currently marked as self-hostable. Claude Fable 5.1 is not marked open weight; Llama 3.1 70B is open weight.
Can Claude Fable 5.1 and Llama 3.1 70B understand images?+
Claude Fable 5.1 is documented with image input; Llama 3.1 70B is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Fable 5.1 or Llama 3.1 70B?+
Neither has a larger sourced maximum output. Claude Fable 5.1 is 128K and Llama 3.1 70B is —.
Do Claude Fable 5.1 and Llama 3.1 70B support reasoning and tool use?+
Claude Fable 5.1: reasoning, tool calling, and image input. Llama 3.1 70B: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Fable 5.1 or Llama 3.1 70B?+
Claude Fable 5.1 has 1 sourced provider route; Llama 3.1 70B has 1, a tie.
Which offers better value, Claude Fable 5.1 or Llama 3.1 70B?+
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.