Llama 4 Scout 17B 16E vs Grok 4.5
At a Glance
| Compare | Grok 4.5xAI | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #25 of 4660.1 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #15 of 44$0.063 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #11 of 3859.2 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $2.00Xai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $6.00Xai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 10,000K | 500K |
| 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-4-Scout-17B-16E | Grok 4.5 |
|---|---|---|
| Developer | Meta | xAI |
| Family | Llama 4 Scout 17b 16e | Grok 4 |
| Model | Llama-4-Scout-17B-16E | Grok 4.5 |
| Version | Llama-4-Scout-17B-16E | Grok 4.5 |
| Lifecycle | active | active |
| Released | 2025-04-05 | 2026-07-16 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 10,000K | 500K |
| Total parameters | 108.6B | Unknown |
| Active parameters | 17B | Unknown |
| License | other | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Together Ai (Standard) | Xai (Standard) |
| Capabilities | chat, generation, tools | chat, generation, reasoning, structured_outputs, tools |
Llama 4 Scout 17B 16E Capabilities
Grok 4.5 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Llama 4 Scout 17B 16E vs Grok 4.5 FAQs
Is Llama 4 Scout 17B 16E or Grok 4.5 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Scout 17B 16E and Grok 4.5, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Llama 4 Scout 17B 16E or Grok 4.5?+
Only Grok 4.5 has a directly sourced input price: $2.00 per million tokens. Only Grok 4.5 has a directly sourced output price: $6.00 per million tokens.
Which has a larger context window, Llama 4 Scout 17B 16E or Grok 4.5?+
Llama 4 Scout 17B 16E has the larger sourced context window. Llama 4 Scout 17B 16E supports 10,000K and Grok 4.5 supports 500K.
Which performs better in benchmarks, Llama 4 Scout 17B 16E or Grok 4.5?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Llama 4 Scout 17B 16E or Grok 4.5 be self-hosted?+
Llama 4 Scout 17B 16E is the only model in this pair currently marked as self-hostable. Llama 4 Scout 17B 16E is open weight; Grok 4.5 is not marked open weight.
Can Llama 4 Scout 17B 16E and Grok 4.5 understand images?+
Llama 4 Scout 17B 16E is documented with image input; Grok 4.5 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama 4 Scout 17B 16E or Grok 4.5?+
Neither has a larger sourced maximum output. Llama 4 Scout 17B 16E is — and Grok 4.5 is —.
Do Llama 4 Scout 17B 16E and Grok 4.5 support reasoning and tool use?+
Llama 4 Scout 17B 16E: tool calling and image input. Grok 4.5: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Llama 4 Scout 17B 16E or Grok 4.5?+
Llama 4 Scout 17B 16E has 1 sourced provider route; Grok 4.5 has 1, a tie.
Which offers better value, Llama 4 Scout 17B 16E or Grok 4.5?+
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.