Llama 3.3 70B Instruct vs Llama 4 Scout 17B 16E
At a Glance
| Compare | ||
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.10Openrouter ↗ · Sep 22, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $0.32Openrouter ↗ · Sep 22, 2026 | Not reported |
| Context windowMaximum documented tokens | 131K | 10,000K |
| Model facts checked | Aug 28, 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 | Llama-3.3-70B-Instruct | Llama-4-Scout-17B-16E |
|---|---|---|
| Developer | Meta | Meta |
| Family | Llama 3 3 70b Instruct | Llama 4 Scout 17b 16e |
| Model | Llama-3.3-70B-Instruct | Llama-4-Scout-17B-16E |
| Version | Llama-3.3-70B-Instruct | Llama-4-Scout-17B-16E |
| Lifecycle | active | active |
| Released | 2024-12-06 | 2025-04-05 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 131K | 10,000K |
| Total parameters | 70.6B | 108.6B |
| Active parameters | Unknown | 17B |
| License | llama3.3 | other |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Together Ai (Standard) |
| Capabilities | chat, generation, tools | chat, generation, tools |
Llama 3.3 70B Instruct Capabilities
Llama 4 Scout 17B 16E Capabilities
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Primary Evidence
Sources and Freshness
Questions
Llama 3.3 70B Instruct vs Llama 4 Scout 17B 16E FAQs
Is Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 3.3 70B Instruct and Llama 4 Scout 17B 16E, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E?+
Only Llama 3.3 70B Instruct has a directly sourced input price: $0.10 per million tokens. Only Llama 3.3 70B Instruct has a directly sourced output price: $0.32 per million tokens.
Which has a larger context window, Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E?+
Llama 4 Scout 17B 16E has the larger sourced context window. Llama 3.3 70B Instruct supports 131K and Llama 4 Scout 17B 16E supports 10,000K.
Which performs better in benchmarks, Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E be self-hosted?+
Both models have the same recorded self-hosting status: supported. Llama 3.3 70B Instruct is open weight; Llama 4 Scout 17B 16E is open weight.
Can Llama 3.3 70B Instruct and Llama 4 Scout 17B 16E understand images?+
Llama 3.3 70B Instruct is not documented with image input; Llama 4 Scout 17B 16E is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E?+
Neither has a larger sourced maximum output. Llama 3.3 70B Instruct is — and Llama 4 Scout 17B 16E is —.
Do Llama 3.3 70B Instruct and Llama 4 Scout 17B 16E support reasoning and tool use?+
Llama 3.3 70B Instruct: tool calling. Llama 4 Scout 17B 16E: tool calling and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E?+
Llama 3.3 70B Instruct has 3 sourced provider routes; Llama 4 Scout 17B 16E has 1, so Llama 3.3 70B Instruct has broader tracked availability.
Which offers better value, Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E?+
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.