--- title: "Meta: Llama 4 Scout — unrated, priced in this catalogue · Undominated.ai" canonical: https://undominated.ai/models/meta-llama__llama-4-scout/ description: "Meta: Llama 4 Scout: $0.100/M in, $0.300/M out. No independent quality score in this catalogue — unrated, not ranked, not scored zero." --- # Meta: Llama 4 Scout — unrated, priced in this catalogue · Undominated.ai > Meta: Llama 4 Scout: $0.100/M in, $0.300/M out. No independent quality score in this catalogue — unrated, not ranked, not scored zero. [Check base rates for this workload](/check/meta-llama__llama-4-scout/) [Cheaper alternatives](/alternatives/) [Family](/families/llama/) [Compare models](https://undominated.ai/compare/?models=meta-llama%2Fllama-4-scout) Comparison context Choose up to three standard models in Compare. Requirements and prompt length apply in Compare. This page keeps its stated price basis and workload controls. MODEL PROOF # Llama 4 Scout Meta · 05 Apr 2025 · llama-4-community Balanced Summarise Chat Code gen Agentic NOT INDEPENDENTLY RATED ## No independent LMArena score is published for this model. **$0.150** / 1M tokens Balanced · 3 tokens in per 1 out Serving precision differs between offers. Evidence as of 06 Oct 2026 [openrouter/models](https://openrouter.ai/api/v1/models) [Vendor cross-check](https://openrouter.ai/api/v1/models) Independent LMArena score Not independently rated Context window 1.31M Maximum output 16.38K Input modalities text, image Output modalities text Published input price $0.100 / 1M tokens Published output price $0.300 / 1M tokens Pricing kind fixed Inspect [complete billing conditions](#billing-details) and endpoint terms below. Price from DeepInfra: the cheapest offer that is serving, at standard delivery and at a declared precision that is not 4-bit (fp8), at its standard rate. The maker’s own precision is not known. Every price dimension · USD per million tokens | Input | $0.100 /M | | --- | --- | | Output | $0.300 /M | | Cached input | Unknown /M | | Cache write | Unknown /M | | Cache write 1h | Unknown /M | | Reasoning | Unknown /M | ### Who sells it The same weights, different shops. Cheapest is not like-for-like when serving precision differs. Headline cheapest is a lower precision. Like-for-like at the best declared precision is $0.180/M from Novita. 3 provider offers · rates, limits and conditions Rates are USD per million tokens. Endpoint terms can differ even when the quoted price and precision match. A listed parameter is a provider declaration, not a task-success test. | Seller | Input | Output | Precision | Uptime (1d) | | --- | --- | --- | --- | --- | | Seller DeepInfra deepinfra/fp8 Endpoint terms Cached input /M Unknown Context limit 327,680 tokens Output limit 16,384 tokens Tools Not listed by endpoint Reasoning Not listed by endpoint Promotional discount None reported Uptime · last 30 minutes 99.98% | Input $0.100 | Output $0.300 | Precision fp8 | Uptime (1d) 99.93% | | Seller Novita novita/bf16 Endpoint terms Cached input /M Unknown Context limit 131,072 tokens Output limit 117,964 tokens Tools Not listed by endpoint Reasoning Not listed by endpoint Promotional discount None reported Uptime · last 30 minutes 99.77% | Input $0.180 | Output $0.590 | Precision bf16 | Uptime (1d) 99.95% | | Seller Google google-vertex/us-east5 Endpoint terms Cached input /M Unknown Context limit 1,310,720 tokens Output limit 8,192 tokens Tools Listed by endpoint Reasoning Not listed by endpoint Promotional discount None reported Uptime · last 30 minutes Unknown | Input $0.250 | Output $0.700 | Precision undeclared | Uptime (1d) — | ### Independent scores No independent benchmark has measured this model. Unrated is not a score of zero. #### Best rankings by task - Data visualisation #120 901 - UI components #124 774 - Code categories #127 795 - Game development #127 786 - Websites #134 757 Per-task Elo and rank from [Design Arena](https://designarena.ai), via OpenRouter’s model feed. The rank is the feed’s, and it counts models OpenRouter does not list. ### Capability | Context window | 1.3M | | --- | --- | | Max output | 16K | | Input modes | text, image | | Tool use | yes | | Reasoning | no | | Knowledge cutoff | 2024-08-31 | | Open weights | yes | ### Provenance | Price source | [openrouter.ai](https://openrouter.ai/api/v1/models) | | --- | --- | | Fetched | 2026-10-06 | | Quality data | unrated | | Cross-checked | [vendor page](https://openrouter.ai/api/v1/models) | Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input... ## Questions this page answers What does Llama 4 Scout cost? $0.100/M in, $0.300/M out in this catalogue, as of the fetch date on this page. That is the API row, not a subscription. Does Llama 4 Scout have an independent quality score? Llama 4 Scout has no independent quality score in this catalogue. Unrated is not a score of zero. What beats Llama 4 Scout? Llama 4 Scout has no independent quality score. Unrated is not a score of zero. Does this page use Artificial Analysis scores for Llama 4 Scout? No. Artificial Analysis figures are not published here. Quality on this page is LMArena Elo where a score exists; otherwise the row is unrated. Does a missing score mean Llama 4 Scout scored zero? Unrated is not a score of zero. Is the cheapest Llama 4 Scout endpoint the same product? Headline cheapest is a lower precision. Like-for-like at the best declared precision is $0.180/M from Novita. MODEL MONUMENT ## Save or share this proof Download proof card · 1200 × 630 Preview and more sharing options Meta: Llama 4 Scout. Balanced workload. Not independently rated. Evidence as of 06 Oct 2026. Copy model link Download square card · 1080 × 1080 Copy landscape image Share landscape card ## Related No independent quality score, so there is no dominator to name. Unrated is not a clean bill of health. - Side by side [Llama 4 Maverick](/compare/meta-llama__llama-4-maverick--vs--meta-llama__llama-4-scout/) - Same vendor [Muse Spark 1.3](/models/meta__muse-spark-1.3/) - Meta models [Meta](/providers/meta/) - Where this model appears [wire](/wire/) - Same vendor [Muse Spark 1.2](/models/meta__muse-spark-1.2/) - Where this model appears [self-host](/self-host/) - Same vendor [Muse Spark 1.1](/models/meta__muse-spark-1.1/) - Where this model appears [spreads](/spreads/) - Where this model appears [traps](/traps/) ## Badge The verdict as one SVG, for a README or a docs page. It states this model's dominance status at the balanced workload on the LMArena lens, with the date it was computed, and it is rebuilt with the catalogue — so it changes when the verdict changes, including to one you would rather it did not. Markdown Copy [![Llama 4 Scout — Undominated.ai dominance verdict](https://undominated.ai/badge/meta-llama__llama-4-scout.svg)](https://undominated.ai/models/meta-llama__llama-4-scout/) HTML Copy Llama 4 Scout — Undominated.ai dominance verdict Direct file: [https://undominated.ai/badge/meta-llama__llama-4-scout.svg](https://undominated.ai/badge/meta-llama__llama-4-scout.svg) — a static SVG, written by scripts/build-badges.mjs on every build, so the copy you embed is never older than the last deploy. ## Continue your investigation - [Explore model families](/families/) - [Compare a shortlist](/compare/) - [Check a model](/check/) - [Understand the evidence](/methodology/)