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Hermes 3 405B Instruct vs Llama 4 Scout

Detailed technical comparison between Hermes 3 405B Instruct (Nous Research) and Llama 4 Scout (Meta). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.

⚡ Executive Summary & Verdict

Comparison Snapshot

Hermes 3 405B Instruct: 0 WinsvsLlama 4 Scout: 6 Wins
Context Leader

Llama 4 Scout

1,310,720 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

Llama 4 Scout

$0.10 / MTok
Nous Researchactive

Hermes 3 405B Instruct

Hermes 3 is a generalist language model with many improvements over Hermes 2, including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the...

View Hermes 3 405B Instruct Full Specs →
Metaactive

Llama 4 Scout

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...

View Llama 4 Scout Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationHermes 3 405B InstructLlama 4 Scout
ProviderNous ResearchMeta
Context Window131,072 tokens1,310,720 tokens🏆
Agent SuitabilityN/A82/100
Time to First Token (TTFT)N/A350 ms
Deployment Modelself hostableself hostable
Production Stabilitystablebeta
API AvailableYesYes
Released Date2024-08-162025-04-05

API Pricing Comparison

Input Price per Million Tokens

Hermes 3 405B Instruct

$1.00

Llama 4 Scout

$0.10

Output Price per Million Tokens

Hermes 3 405B Instruct

$1.00

Llama 4 Scout

$0.30

💡 Cost Ratio: Llama 4 Scout is 10.0x cheaper per input token than Hermes 3 405B Instruct.

Want to test both models live?

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Benchmark Performance Metrics

Standardized Scores (0–100%)

Scores show verified raw accuracy percentages across standardized AI evaluation suites. Higher bars indicate superior performance in that domain.

MMLUGeneral knowledge & multi-task understanding
78.8%vs87.2%+8.4% Llama 4 Scout
Hermes 3 405B Instruct
Llama 4 Scout 🏆
HumanEvalPython coding & logic synthesis
77.0%vs89.5%+12.5% Llama 4 Scout
Hermes 3 405B Instruct
Llama 4 Scout 🏆
MATHComplex mathematical problem solving
54.2%vs81.0%+26.8% Llama 4 Scout
Hermes 3 405B Instruct
Llama 4 Scout 🏆
GPQAGraduate-level expert reasoning
39.6%vs66.8%+27.2% Llama 4 Scout
Hermes 3 405B Instruct
Llama 4 Scout 🏆
HellaSwagCommonsense reasoning and inference
81.8%vs94.5%+12.7% Llama 4 Scout
Hermes 3 405B Instruct
Llama 4 Scout 🏆
MT-BenchMulti-turn conversation flow quality
8.4%vs9.1%+0.7% Llama 4 Scout
Hermes 3 405B Instruct
Llama 4 Scout 🏆

Hermes 3 405B Instruct Quirks & Gotchas

No developer gotchas reported.

Llama 4 Scout Quirks & Gotchas

  • ▸10M context causes significant VRAM pressure — recommend 4-bit quantization
  • ▸Primarily designed for RAG, not agentic tool calling

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