Claude Opus 4.6 vs Llama 3.1 8B Instruct
At a Glance
| Compare | Claude Opus 4.6Anthropic | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #12 of 4676.2 score · 3/3 sources · complete | UnrankedNot in the 46-model eligible cohort |
| CostLower is better · Published-token output estimate | #33 of 44$0.241 per LiveBench case | UnrankedNot in the 44-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.5 | #19 of 3853.2 score · 3/3 sources · complete | UnrankedNot in the 38-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $5.00Anthropic ↗ · Sep 3, 2026 | $0.050Openrouter ↗ · Sep 23, 2026 |
| Output priceFrom · USD / 1M tokens | $25.00Anthropic ↗ · Sep 3, 2026 | $0.080Openrouter ↗ · Sep 23, 2026 |
| Context windowMaximum documented tokens | 1,000K | 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
| Benchmark | Claude Opus 4.6 | Llama-3.1-8B-Instruct |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,497.54100% of row best · rating · claude-opus-4-6; 95% CI [1494.14263199, 1500.94441396]; votes 75878; rank 5 | 1,186.4879% of row best · rating · llama-3.1-8b-instruct; 95% CI [1182.38141125, 1190.58254982]; votes 49605; rank 313 |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 84.21100% of row best · points · Claude Opus 4.6 · 13,556 output tokens / case | 47.9257% of row best · points · Llama 3.1 8B · 1,165 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 1 benchmark winNo overall winner | 0 benchmark winsNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Claude Opus 4.6 | Llama-3.1-8B-Instruct |
|---|---|---|
| Developer | Anthropic | Meta |
| Family | Claude 4 | Llama 3 1 8b Instruct |
| Model | Claude Opus 4.6 | Llama-3.1-8B-Instruct |
| Version | Claude Opus 4.6 | Llama-3.1-8B-Instruct |
| Lifecycle | active | active |
| Released | 2026-02-05 | 2024-07-23 |
| Knowledge cutoff | 2025-05-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 131K |
| Total parameters | Unknown | 8B |
| 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), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, tools |
Claude Opus 4.6 Capabilities
Llama 3.1 8B Instruct Capabilities
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|---|---|---|---|
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Claude Opus 4.6Anthropic | vs |  DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
Claude Opus 4.6Anthropic | vs | Grok 4.6xAI | cross-developer peersimage, text |
Claude Opus 4.6Anthropic | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text |
Claude Opus 4.6Anthropic | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | Claude Opus 4.6Anthropic | cross-developer peersimage, text |
Claude Opus 4.6Anthropic | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Claude Opus 4.6Anthropic | vs |  Hy4 previewTencent | cross-developer peerstext |
Claude Opus 4.6Anthropic | vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text |
Claude Opus 4.6Anthropic | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Claude Opus 4.6 vs Llama 3.1 8B Instruct FAQs
Is Claude Opus 4.6 or Llama 3.1 8B Instruct better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.6 and Llama 3.1 8B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Opus 4.6 or Llama 3.1 8B Instruct?+
Claude Opus 4.6 is $5.00 and Llama 3.1 8B Instruct is $0.050 per million tokens, so Llama 3.1 8B Instruct is cheaper on this metric. Claude Opus 4.6 is $25.00 and Llama 3.1 8B Instruct is $0.080 per million tokens, so Llama 3.1 8B Instruct is cheaper on this metric.
Which has a larger context window, Claude Opus 4.6 or Llama 3.1 8B Instruct?+
Claude Opus 4.6 has the larger sourced context window. Claude Opus 4.6 supports 1,000K and Llama 3.1 8B Instruct supports 131K.
Which performs better in benchmarks, Claude Opus 4.6 or Llama 3.1 8B Instruct?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Claude Opus 4.6 or Llama 3.1 8B Instruct be self-hosted?+
Llama 3.1 8B Instruct is the only model in this pair currently marked as self-hostable. Claude Opus 4.6 is not marked open weight; Llama 3.1 8B Instruct is open weight.
Can Claude Opus 4.6 and Llama 3.1 8B Instruct understand images?+
Claude Opus 4.6 is documented with image input; Llama 3.1 8B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Opus 4.6 or Llama 3.1 8B Instruct?+
Neither has a larger sourced maximum output. Claude Opus 4.6 is 128K and Llama 3.1 8B Instruct is —.
Do Claude Opus 4.6 and Llama 3.1 8B Instruct support reasoning and tool use?+
Claude Opus 4.6: reasoning, tool calling, and image input. Llama 3.1 8B Instruct: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Opus 4.6 or Llama 3.1 8B Instruct?+
Claude Opus 4.6 has 1 sourced provider route; Llama 3.1 8B Instruct has 2, so Llama 3.1 8B Instruct has broader tracked availability.
Which offers better value, Claude Opus 4.6 or Llama 3.1 8B 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.