Llama 4 Scout 17B 16E Instruct vs GPT-4.1 Nano
At a Glance
| Compare |  GPT-4.1 NanoOpenAI | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.10Deepinfra ↗ · Sep 21, 2026 | $0.050Openrouter ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $0.30Deepinfra ↗ · Sep 21, 2026 | $0.20Openrouter ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 10,000K | 1,048K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 29, 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-4.1 Nano |
|---|---|---|
| Berkeley Function Calling Leaderboardv4-ede5081a24bc · overall_accuracy · leader | 28.13100% of row best · percent · Llama-4-Scout-17B-16E-Instruct (FC) | 24.8888% of row best · percent · GPT-4.1-nano-2025-04-14 (Prompt) |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · statistical tie | 1,279.29100% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1274.57681953, 1284.00026285]; votes 29740; rank 259 | 1,284.72100% of row best · rating · gpt-4.1-nano-2025-04-14; 95% CI [1277.08013307, 1292.36659971]; votes 6103; rank 250 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,117.80100% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1108.35603674, 1127.24229078]; votes 6466; rank 114 | 1,063.1495% of row best · rating · gpt-4.1-nano-2025-04-14; 95% CI [1044.85853307, 1081.42105669]; votes 1211; rank 124 |
| Overall ResultCounted from the protocol-matched rows above · 1 tie | 2 benchmark winsOverall lead | 0 benchmark wins |
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-4.1 Nano |
|---|---|---|
| Developer | Meta | OpenAI |
| Family | Llama 4 Scout 17b 16e Instruct | Gpt 4 1 |
| Model | Llama-4-Scout-17B-16E-Instruct | GPT-4.1 Nano |
| Version | Llama-4-Scout-17B-16E-Instruct | GPT-4.1 Nano |
| Lifecycle | active | active |
| Released | 2025-04-05 | Unknown |
| Knowledge cutoff | Unknown | 2024-06-01 |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 10,000K | 1,048K |
| 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, tools |
Llama 4 Scout 17B 16E Instruct Capabilities
GPT-4.1 Nano Capabilities
Related Comparisons
All image comparisons →| A | Pair | B | Context |
|---|---|---|---|
| vs | GPT-6 AstraOpenAI | cross-developer peersimage, text | |
Claude Fable 5.1Anthropic | vs | cross-developer peersimage, text | |
 Gemini 3.1 ProGoogle DeepMind | vs | cross-developer peerstext | |
 DeepSeek-V4.1-FlashDeepSeek | vs | cross-developer peersimage, text | |
| vs | Grok 4.6xAI | cross-developer peersimage, text | |
| vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text | |
| vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text | |
 MiniMax-M3MiniMax | vs | cross-developer peersimage, text | |
| vs |  GLM-5.3Z.ai | cross-developer peerstext | |
| vs |  Hy4 previewTencent | cross-developer peerstext | |
Seed 2.1 ProByteDance Seed | vs | cross-developer peersimage, text | |
| vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Llama 4 Scout 17B 16E Instruct vs GPT-4.1 Nano FAQs
Is Llama 4 Scout 17B 16E Instruct or GPT-4.1 Nano better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Scout 17B 16E Instruct and GPT-4.1 Nano, 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-4.1 Nano?+
Llama 4 Scout 17B 16E Instruct is $0.10 and GPT-4.1 Nano is $0.050 per million tokens, so GPT-4.1 Nano is cheaper on this metric. Llama 4 Scout 17B 16E Instruct is $0.30 and GPT-4.1 Nano is $0.20 per million tokens, so GPT-4.1 Nano is cheaper on this metric.
Which has a larger context window, Llama 4 Scout 17B 16E Instruct or GPT-4.1 Nano?+
Llama 4 Scout 17B 16E Instruct has the larger sourced context window. Llama 4 Scout 17B 16E Instruct supports 10,000K and GPT-4.1 Nano supports 1,048K.
Which performs better in benchmarks, Llama 4 Scout 17B 16E Instruct or GPT-4.1 Nano?+
Llama 4 Scout 17B 16E Instruct leads the current overall benchmark count. The result uses 3 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.
Can Llama 4 Scout 17B 16E Instruct or GPT-4.1 Nano be self-hosted?+
Llama 4 Scout 17B 16E Instruct is the only model in this pair currently marked as self-hostable. Llama 4 Scout 17B 16E Instruct is open weight; GPT-4.1 Nano is not marked open weight.
Can Llama 4 Scout 17B 16E Instruct and GPT-4.1 Nano understand images?+
Llama 4 Scout 17B 16E Instruct is documented with image input; GPT-4.1 Nano 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-4.1 Nano?+
Neither has a larger sourced maximum output. Llama 4 Scout 17B 16E Instruct is — and GPT-4.1 Nano is 33K.
Do Llama 4 Scout 17B 16E Instruct and GPT-4.1 Nano support reasoning and tool use?+
Llama 4 Scout 17B 16E Instruct: tool calling and image input. GPT-4.1 Nano: 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-4.1 Nano?+
Llama 4 Scout 17B 16E Instruct has 4 sourced provider routes; GPT-4.1 Nano 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-4.1 Nano?+
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.