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Grok 4.5 vs Llama 4 Scout

Compare Grok 4.5 from Grok and Llama 4 Scout from Llama on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.

GrokGrok 4.5LlamaLlama 4 Scout
Grok logo
Grok 4.5
Grok · text, image → text

Grok 4.5 was trained on datasets spanning knowledge in coding, science, engineering, and math. With both intelligent and efficient reasoning, Grok 4.5 excels at real engineering tasks and exceeds comparable leading models at these tasks.

Input$2 /M
Output$6 /M
Cache read$0.5 /M
Llama logo
Llama 4 Scout
Llama · text, image → text

Llama 4 Scout is a highly efficient Mixture-of-Experts (MoE) model from Meta, activating 17B out of 109B total parameters per inference. It natively supports multimodal input (text and image) and multilingual output (text and code) across 12 languages. Designed for assistant-style interaction and visual reasoning, Scout features a massive 10-million-token context window. It is instruction-tuned for tasks like multilingual chat and image understanding and is released under the Llama 4 Community License for local or commercial deployment.

Input$0.2 /M
Output$0.2 /M

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

Grok 4.5
Llama 4 Scout
Input /M
$2
$0.2
Output /M
$6
$0.2
Cache read /M
$0.5
-
Context length
500,000
131,072
Max output
500,000
131,000
Time to First Token
1.6 s
0.4 s
Throughput
17.6 tok/s
147.6 tok/s
Modalities
textimage
textimage
Supported Parameters
thinkingtoolsfunction callingstructured outputslong context
toolsfunction callingstructured outputs
API Formats
Released
July 2026
April 5, 2025

Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

grok-4.5llama-4-scout

Tokens / day

-

Requests / day

-

Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

grok-4.5llama-4-scout

Throughput (tok/s)

-

TTFT (s)

-

Uptime (%)

-

LMArena Benchmarks

LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.

Text
grok-4.5llama-4-scout
12601320138014401500
Overall
13231466
Coding
13621362
Math
13091309
Hard prompts
13301330
Instruction following
13001300
Multi-turn
13201320
Creative writing
12901290
Longer query
13271327
Chinese
13151315
English
13411341
Vision
grok-4.5llama-4-scout
1100116012201280
Overall
11281280
OCR
11291129
Diagram
11471147
Homework
11491149

Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.

Cost calculator

Estimate your monthly bill for the same workload on each model.

Llama 4 Scout
$15.00 /mo
Grok 4.5
$210 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: Grok 4.5, Llama 4 Scout?

Llama 4 Scout: $0.2/M output tokens; Grok 4.5: $6/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

Llama 4 Scout: 0.4s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

Grok 4.5 accepts 500,000 and Llama 4 Scout accepts 131,072 input tokens. Maximum output per request is 500,000 tokens on Grok 4.5 and 131,000 tokens on Llama 4 Scout.

Which one generates tokens faster?

Llama 4 Scout at 147.6 tok/s and Grok 4.5 at 17.6 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

Grok 4.5 accepts text and image input and supports thinking, tool calling, function calling, structured outputs and long context; Llama 4 Scout accepts text and image input and supports tool calling, function calling and structured outputs.

Can I call Grok 4.5 and Llama 4 Scout with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

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