Llama 4 Scout 17B 16E Instruct vs GPT-5.6 Luna
At a Glance
| Compare |  GPT-5.6 LunaOpenAI | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v4.4 | #43 of 570.0 score · 1/3 sources · single-source provisional · missing LiveBench, ARC-AGI-2 · full-core range 0.0–66.7 | UnrankedNot in the 57-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.10Deepinfra ↗ · Oct 19, 2026 | $0.20Openai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $0.30Deepinfra ↗ · Oct 19, 2026 | $1.20Openai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 10,000K | 1,050K |
| 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-4-Scout-17B-16E-Instruct | GPT-5.6 Luna |
|---|---|---|
| LMArena Text Arenatext-2026-10-15-0ebb411abf00 · arena_rating · leader | 1,279.1689% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1274.44779094, 1283.86814615]; votes 29826; rank 273 | 1,430.66100% of row best · rating · gpt-5.6-luna-xhigh; 95% CI [1426.38028671, 1434.93119450]; votes 41109; rank 93 |
| LMArena Vision Arenavision-2026-10-09-0ebb411abf00 · arena_rating · leader | 1,118.2389% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1108.78959993, 1127.66568063]; votes 6451; rank 127 | 1,258.24100% of row best · rating · gpt-5.6-luna-xhigh; 95% CI [1250.82216689, 1265.66350676]; votes 11086; rank 58 |
| ToneBench2026-10-17-10-task-e9c76358afb2 · overall_score · unverified | 37.5948% of row best · points · Llama 4 Scout (no thinking) · 847 output tokens / case | 78.83100% of row best · points · GPT-5.6 Luna (ultra) · 19,621 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 2 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-4-Scout-17B-16E-Instruct | GPT-5.6 Luna |
|---|---|---|
| Developer | Meta | OpenAI |
| Family | Llama 4 Scout 17b 16e Instruct | Gpt 5 6 |
| Model | Llama-4-Scout-17B-16E-Instruct | GPT-5.6 Luna |
| Version | Llama-4-Scout-17B-16E-Instruct | GPT-5.6 Luna |
| Lifecycle | active | active |
| Released | 2025-04-05 | Unknown |
| Knowledge cutoff | Unknown | 2026-02-16 |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 10,000K | 1,050K |
| 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 | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, tools | chat, generation, reasoning, tools |
Llama 4 Scout 17B 16E Instruct Capabilities
GPT-5.6 Luna Capabilities
Related Comparisons
All image comparisons →| A | Pair | B | Context |
|---|---|---|---|
| vs | family variantsimage, text | ||
| vs | cross-developer peersimage, text | ||
 Llama-3.1-405BMeta | vs | family variantstext | |
| vs | family variantsimage, text | ||
| vs |  Ministral-3-14B-Instruct-2512Mistral AI | cross-developer peersimage, text | |
| vs | Mistral-Medium-3.5-128BMistral AI | cross-developer peersimage, text | |
| vs | Mistral-Small-4-119B-2603Mistral AI | cross-developer peersimage, text | |
| vs | GPT-4oOpenAI | cross-developer peersimage, text | |
| vs | GPT-4o MiniOpenAI | cross-developer peersimage, text | |
| vs | GPT-5 ProOpenAI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Llama 4 Scout 17B 16E Instruct vs GPT-5.6 Luna FAQs
Is Llama 4 Scout 17B 16E Instruct or GPT-5.6 Luna better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Scout 17B 16E Instruct and GPT-5.6 Luna, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Llama 4 Scout 17B 16E Instruct or GPT-5.6 Luna?+
Llama 4 Scout 17B 16E Instruct is $0.10 and GPT-5.6 Luna is $0.20 per million tokens, so Llama 4 Scout 17B 16E Instruct is cheaper on this metric. Llama 4 Scout 17B 16E Instruct is $0.30 and GPT-5.6 Luna is $1.20 per million tokens, so Llama 4 Scout 17B 16E Instruct is cheaper on this metric.
Which has a larger context window, Llama 4 Scout 17B 16E Instruct or GPT-5.6 Luna?+
Llama 4 Scout 17B 16E Instruct has the larger sourced context window. Llama 4 Scout 17B 16E Instruct supports 10,000,000 tokens and GPT-5.6 Luna supports 1,050,000 tokens.
Which performs better in benchmarks, Llama 4 Scout 17B 16E Instruct or GPT-5.6 Luna?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Llama 4 Scout 17B 16E Instruct or GPT-5.6 Luna be self-hosted?+
Llama 4 Scout 17B 16E Instruct is documented as self-hostable; GPT-5.6 Luna is documented as not self-hostable. Llama 4 Scout 17B 16E Instruct is open weight; GPT-5.6 Luna is not marked open weight.
Can Llama 4 Scout 17B 16E Instruct and GPT-5.6 Luna understand images?+
Llama 4 Scout 17B 16E Instruct is documented with image input; GPT-5.6 Luna is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama 4 Scout 17B 16E Instruct or GPT-5.6 Luna?+
GPT-5.6 Luna has a sourced maximum output of 128,000 tokens; Llama 4 Scout 17B 16E Instruct's maximum output is not reported. A larger limit cannot be determined.
Do Llama 4 Scout 17B 16E Instruct and GPT-5.6 Luna support reasoning and tool use?+
Llama 4 Scout 17B 16E Instruct: tool calling and image input. GPT-5.6 Luna: 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 Instruct or GPT-5.6 Luna?+
Llama 4 Scout 17B 16E Instruct has 4 sourced provider routes; GPT-5.6 Luna has 2, so Llama 4 Scout 17B 16E Instruct has broader tracked availability.
Which offers better value, Llama 4 Scout 17B 16E Instruct or GPT-5.6 Luna?+
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.