โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Llama 4 Scout vs Qwen3.6 Flash

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Llama 4 Scout and Qwen3.6 Flash.

Meta

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 Full Specs
Alibaba

Qwen3.6 Flash

Qwen3.6 Flash is a fast, efficient language model from Alibaba's Qwen 3.6 series. It supports text, image, and video input with a 1M token context window. Tiered pricing kicks in...

View Full Specs

Technical Specifications

SpecificationLlama 4 ScoutQwen3.6 Flash
ProviderMetaAlibaba
Context Window10,000,000 tokens1,000,000 tokens
Agent Suitability82/100N/A
Time to First Token (TTFT)350 msN/A
Deployment Modelself hostableself hostable
Production Stabilitybetabeta
API AvailableYesYes
Released Date2025-04-052026-04-27

API Pricing Comparison

Input Price per Million Tokens

Llama 4 Scout

$0.10

Qwen3.6 Flash

$0.19

Output Price per Million Tokens

Llama 4 Scout

$0.30

Qwen3.6 Flash

$1.13

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8720.0%vsN/A
Llama 4 Scout
Qwen3.6 Flash
HumanEvalPython coding & logic synthesis
8950.0%vsN/A
Llama 4 Scout
Qwen3.6 Flash
MATHComplex mathematical problem solving
8100.0%vsN/A
Llama 4 Scout
Qwen3.6 Flash
GPQAGraduate-level expert reasoning
6680.0%vsN/A
Llama 4 Scout
Qwen3.6 Flash
HellaSwagCommonsense reasoning and inference
9450.0%vsN/A
Llama 4 Scout
Qwen3.6 Flash
MT-BenchMulti-turn conversation flow quality
910.0%vsN/A
Llama 4 Scout
Qwen3.6 Flash

Llama 4 Scout Quirks & Gotchas

  • โ–ธ10M context causes significant VRAM pressure โ€” recommend 4-bit quantization
  • โ–ธPrimarily designed for RAG, not agentic tool calling

Qwen3.6 Flash Quirks & Gotchas

No developer gotchas reported.