Llama 3.3 70B Instruct vs Llama 4 Scout 17B 16E Instruct
At a Glance
| Compare | ||
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.10Openrouter ↗ · Sep 22, 2026 | $0.10Deepinfra ↗ · Sep 21, 2026 |
| Output priceFrom · USD / 1M tokens | $0.32Openrouter ↗ · Sep 22, 2026 | $0.30Deepinfra ↗ · Sep 21, 2026 |
| 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
| Benchmark | Llama-3.3-70B-Instruct | Llama-4-Scout-17B-16E-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboardv4-ede5081a24bc · overall_accuracy · leader | 31.90100% of row best · percent · Llama-3.3-70B-Instruct (FC) | 28.1388% of row best · percent · Llama-4-Scout-17B-16E-Instruct (FC) |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · statistical tie | 1,273.98100% of row best · rating · llama-3.3-70b-instruct; 95% CI [1270.49383309, 1277.45726344]; votes 54412; rank 262 | 1,279.29100% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1274.57681953, 1284.00026285]; votes 29740; rank 259 |
| Overall ResultCounted from the protocol-matched rows above · 1 tie | 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 | Llama-3.3-70B-Instruct | Llama-4-Scout-17B-16E-Instruct |
|---|---|---|
| Developer | Meta | Meta |
| Family | Llama 3 3 70b Instruct | Llama 4 Scout 17b 16e Instruct |
| Model | Llama-3.3-70B-Instruct | Llama-4-Scout-17B-16E-Instruct |
| Version | Llama-3.3-70B-Instruct | Llama-4-Scout-17B-16E-Instruct |
| 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) | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, tools | chat, generation, tools |
Llama 3.3 70B Instruct Capabilities
Llama 4 Scout 17B 16E Instruct Capabilities
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Primary Evidence
Sources and Freshness
Questions
Llama 3.3 70B Instruct vs Llama 4 Scout 17B 16E Instruct FAQs
Is Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E Instruct 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 Instruct, 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 Instruct?+
Llama 3.3 70B Instruct is $0.10 and Llama 4 Scout 17B 16E Instruct is $0.10 per million tokens, so they are tied on this metric. Llama 3.3 70B Instruct is $0.32 and Llama 4 Scout 17B 16E Instruct is $0.30 per million tokens, so Llama 4 Scout 17B 16E Instruct is cheaper on this metric.
Which has a larger context window, Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E Instruct?+
Llama 4 Scout 17B 16E Instruct has the larger sourced context window. Llama 3.3 70B Instruct supports 131K and Llama 4 Scout 17B 16E Instruct supports 10,000K.
Which performs better in benchmarks, Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E Instruct?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E Instruct 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 Instruct is open weight.
Can Llama 3.3 70B Instruct and Llama 4 Scout 17B 16E Instruct understand images?+
Llama 3.3 70B Instruct is not documented with image input; Llama 4 Scout 17B 16E Instruct 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 Instruct?+
Neither has a larger sourced maximum output. Llama 3.3 70B Instruct is — and Llama 4 Scout 17B 16E Instruct is —.
Do Llama 3.3 70B Instruct and Llama 4 Scout 17B 16E Instruct support reasoning and tool use?+
Llama 3.3 70B Instruct: tool calling. Llama 4 Scout 17B 16E Instruct: 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 Instruct?+
Llama 3.3 70B Instruct has 3 sourced provider routes; Llama 4 Scout 17B 16E Instruct has 4, so Llama 4 Scout 17B 16E Instruct has broader tracked availability.
Which offers better value, Llama 3.3 70B Instruct or Llama 4 Scout 17B 16E 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.