Llama 3.1 70B Instruct vs Grok Build 0.1
At a Glance
| Compare | ||
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #1 of 44$0.0020 per LiveBench case |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.40Openrouter ↗ · Sep 22, 2026 | $1.00Xai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $0.40Openrouter ↗ · Sep 22, 2026 | $2.00Xai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 131K | 256K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 3, 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 | Llama-3.1-70B-Instruct | Grok Build 0.1 |
|---|---|---|
| Developer | Meta | xAI |
| Family | Llama 3 1 70b Instruct | Grok Build |
| Model | Llama-3.1-70B-Instruct | Grok Build 0.1 |
| Version | Llama-3.1-70B-Instruct | Grok Build 0.1 |
| Lifecycle | active | preview |
| Released | 2024-07-23 | 2026-05-29 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 131K | 256K |
| Total parameters | 70.6B | Unknown |
| Active parameters | Unknown | Unknown |
| License | llama3.1 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Openrouter (Standard) | Xai (Standard) |
| Capabilities | chat, generation, tools | chat, generation, reasoning, structured_outputs, tools |
Llama 3.1 70B Instruct Capabilities
Grok Build 0.1 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Llama 3.1 70B Instruct vs Grok Build 0.1 FAQs
Is Llama 3.1 70B Instruct or Grok Build 0.1 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 3.1 70B Instruct and Grok Build 0.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Llama 3.1 70B Instruct or Grok Build 0.1?+
Llama 3.1 70B Instruct is $0.40 and Grok Build 0.1 is $1.00 per million tokens, so Llama 3.1 70B Instruct is cheaper on this metric. Llama 3.1 70B Instruct is $0.40 and Grok Build 0.1 is $2.00 per million tokens, so Llama 3.1 70B Instruct is cheaper on this metric.
Which has a larger context window, Llama 3.1 70B Instruct or Grok Build 0.1?+
Grok Build 0.1 has the larger sourced context window. Llama 3.1 70B Instruct supports 131K and Grok Build 0.1 supports 256K.
Which performs better in benchmarks, Llama 3.1 70B Instruct or Grok Build 0.1?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Llama 3.1 70B Instruct or Grok Build 0.1 be self-hosted?+
Llama 3.1 70B Instruct is the only model in this pair currently marked as self-hostable. Llama 3.1 70B Instruct is open weight; Grok Build 0.1 is not marked open weight.
Can Llama 3.1 70B Instruct and Grok Build 0.1 understand images?+
Llama 3.1 70B Instruct is not documented with image input; Grok Build 0.1 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama 3.1 70B Instruct or Grok Build 0.1?+
Neither has a larger sourced maximum output. Llama 3.1 70B Instruct is — and Grok Build 0.1 is —.
Do Llama 3.1 70B Instruct and Grok Build 0.1 support reasoning and tool use?+
Llama 3.1 70B Instruct: tool calling. Grok Build 0.1: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Llama 3.1 70B Instruct or Grok Build 0.1?+
Llama 3.1 70B Instruct has 1 sourced provider route; Grok Build 0.1 has 1, a tie.
Which offers better value, Llama 3.1 70B Instruct or Grok Build 0.1?+
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.