Llama 3.1 8B 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 | $0.050Openrouter ↗ · Sep 22, 2026 | $1.00Xai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $0.080Openrouter ↗ · 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-3.1-8B-Instruct | Grok Build 0.1 |
|---|---|---|
| Developer | Meta | xAI |
| Family | Llama 3 1 8b Instruct | Grok Build |
| Model | Llama-3.1-8B-Instruct | Grok Build 0.1 |
| Version | Llama-3.1-8B-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 | 8B | Unknown |
| Active parameters | Unknown | Unknown |
| License | llama3.1 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Hugging Face (Standard), Openrouter (Standard) | Xai (Standard) |
| Capabilities | chat, generation, tools | chat, generation, reasoning, structured_outputs, tools |
Llama 3.1 8B Instruct Capabilities
Grok Build 0.1 Capabilities
Primary Evidence
Sources and Freshness
Questions
Llama 3.1 8B Instruct vs Grok Build 0.1 FAQs
Is Llama 3.1 8B 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 8B 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 8B Instruct or Grok Build 0.1?+
Llama 3.1 8B Instruct is $0.050 and Grok Build 0.1 is $1.00 per million tokens, so Llama 3.1 8B Instruct is cheaper on this metric. Llama 3.1 8B Instruct is $0.080 and Grok Build 0.1 is $2.00 per million tokens, so Llama 3.1 8B Instruct is cheaper on this metric.
Which has a larger context window, Llama 3.1 8B Instruct or Grok Build 0.1?+
Grok Build 0.1 has the larger sourced context window. Llama 3.1 8B Instruct supports 131K and Grok Build 0.1 supports 256K.
Which performs better in benchmarks, Llama 3.1 8B 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 8B Instruct or Grok Build 0.1 be self-hosted?+
Llama 3.1 8B Instruct is the only model in this pair currently marked as self-hostable. Llama 3.1 8B Instruct is open weight; Grok Build 0.1 is not marked open weight.
Can Llama 3.1 8B Instruct and Grok Build 0.1 understand images?+
Llama 3.1 8B 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 8B Instruct or Grok Build 0.1?+
Neither has a larger sourced maximum output. Llama 3.1 8B Instruct is — and Grok Build 0.1 is —.
Do Llama 3.1 8B Instruct and Grok Build 0.1 support reasoning and tool use?+
Llama 3.1 8B 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 8B Instruct or Grok Build 0.1?+
Llama 3.1 8B Instruct has 2 sourced provider routes; Grok Build 0.1 has 1, so Llama 3.1 8B Instruct has broader tracked availability.
Which offers better value, Llama 3.1 8B 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.