Verified 2026 API Rates • Prompt Caching & Batch ROI

Meta: Llama 4 Scout vs Qwen: Qwen3 Coder 480B A35B

Compare real-world API costs for Meta: Llama 4 Scout ($0.1/$0.3) vs Qwen: Qwen3 Coder 480B A35B ($0.3/$1). Calculate Prompt Caching ROI & Batch API savings.

Meta: Llama 4 Scout saves up to 67% on base input tokens
Meta

Meta: Llama 4 Scout

llama-4-scout
Base Input Rate
$0.10 / 1M
Output Rate
$0.30 / 1M
Prompt Cache Read
$0.10 / 1M (-0%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
Not Supported
Context Window
1,310.72k tokens
Quality Index (MMLU)
78
Alibaba Qwen

Qwen: Qwen3 Coder 480B A35B

qwen3-coder
Base Input Rate
$0.30 / 1M
Output Rate
$1.00 / 1M
Prompt Cache Read
$0.10 / 1M (-66.67%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
-40% Off
Context Window
262.144k tokens
Quality Index (MMLU)
78
Differential Module 1

Prompt Caching ROI & Write Surcharge Break-Even Analysis

Prompt caching drastically reduces input token costs for static prefixes like system prompts, tool schemas, and document chunks. Compare caching mechanisms between Meta: Llama 4 Scout and Qwen: Qwen3 Coder 480B A35B:

Meta: Llama 4 Scout Caching Profile-0% read discount

  • Cached Read Price: $0.100 per 1M tokens.
  • Write Surcharge: $0.00 (automatic caching with zero write penalty).
  • Minimum Cache Prefix: 1,024 tokens.
  • Amortization Rule: Immediate net savings from first cached read call.

Qwen: Qwen3 Coder 480B A35B Caching Profile-66.67% read discount

  • Cached Read Price: $0.100 per 1M tokens.
  • Write Surcharge: $0.00 (automatic caching with zero write penalty).
  • Minimum Cache Prefix: 1,024 tokens.
  • Amortization Rule: Immediate net savings from first cached read call.
Differential Module 2

Batch API 50% Discount Offload vs Real-Time SLA

Asynchronous Batch APIs cut total token expenditures in half (50% off input and output) in exchange for non-realtime execution (up to 24-hour turnaround SLA).

Model / ArchitectureStandard Input / OutputBatch 50% Off Input / OutputTurnaround SLAOptimal Use Cases
Meta: Llama 4 Scout$0.10 / $0.30Standard on-demand rateInstant real-timeBulk evaluation, dataset labeling, background summarization
Qwen: Qwen3 Coder 480B A35B$0.30 / $1.00$0.15 / $0.50 (-50%)24 Hours max (typically 30m - 2h)Offline document translation, embedding backfills, test suites
Differential Module 3

Context Window Escalation & Tiered Pricing Architecture

Massive context windows allow ingesting entire repositories or books, but pricing models differ drastically between flat-rate vendors and tiered step-up pricing.

Meta: Llama 4 Scout Context Capacity

Provides a 1,310.72k token context window with a maximum output limit of 16.384k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

Qwen: Qwen3 Coder 480B A35B Context Capacity

Provides a 262.144k token context window with a maximum output limit of 65.536k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

Quill Strategic Content

Real-World Production Scenarios: Monthly Spend Projections

Pre-computed monthly engineering bill projections across 3 representative enterprise application workloads:

Scenario 1

RAG Knowledge Base & Enterprise Search

100,000 queries/month, 3,500 input tokens (system + 5 retrieved chunks), 400 output tokens, 75% prompt cache hit rate.

Meta: Llama 4 Scout:$47.00/mo
Qwen: Qwen3 Coder 480B A35B:$92.50/mo
Delta Savings:-$45.50 (49%)
Architecture Verdict:Meta: Llama 4 Scout delivers 49% lower monthly spend ($45.50/mo savings) for this workload profile.
Scenario 2

Multi-Turn Coding Agent & ReAct Loops

25,000 tasks/month, 8,000 input tokens (accumulating conversation context & tool schemas), 1,200 output tokens, 85% cache hit rate.

Meta: Llama 4 Scout:$29.00/mo
Qwen: Qwen3 Coder 480B A35B:$52.64/mo
Delta Savings:-$23.64 (45%)
Architecture Verdict:Meta: Llama 4 Scout delivers 45% lower monthly spend ($23.64/mo savings) for this workload profile.
Scenario 3

High-Throughput Offline Data Extraction

500,000 records/month, 1,500 input tokens, 250 output tokens, 100% batch offload (24-hour turnaround SLA).

Meta: Llama 4 Scout:$112.50/mo
Qwen: Qwen3 Coder 480B A35B:$192.00/mo
Delta Savings:-$79.50 (41%)
Architecture Verdict:Meta: Llama 4 Scout delivers 41% lower monthly spend ($79.50/mo savings) for this workload profile.
ミリ秒単位の対話型シミュレータ

Meta: Llama 4 Scout vs Qwen: Qwen3 Coder 480B A35B

エンタープライズの代表的な3大ユースケース(RAG検索、コーディングAgent、バッチ抽出)で精密試算:

Live 50ms Engine
月間リクエスト数 (Requests)100,000
入力トークン数/回 (Input Tokens)4,000
出力トークン数/回 (Output Tokens)1,000
Prompt キャッシュヒット率 (Cache Hit)70%
Batch API 分流比率0%
Meta: Llama 4 Scout 安価

月間推定削減額

Meta: Llama 4 Scout$70.00$0.700// 1,000リクエスト
vs
Qwen: Qwen3 Coder 480B A35B$164.00$1.640// 1,000リクエスト
Developer FAQs

Frequently Asked Questions: Meta: Llama 4 Scout vs Qwen: Qwen3 Coder 480B A35B

Authoritative answers on API rate limits, pricing math, break-even thresholds, and architectural migration.

1Which model is cheaper overall: Meta: Llama 4 Scout or Qwen: Qwen3 Coder 480B A35B?

At base pricing, Meta: Llama 4 Scout costs $0.1/1M input and $0.3/1M output, while Qwen: Qwen3 Coder 480B A35B costs $0.3/1M input and $1/1M output. The cheaper option depends on your input-to-output token ratio and whether prompt caching or batch discounts are utilized.

2How does Prompt Caching impact the cost of Meta: Llama 4 Scout vs Qwen: Qwen3 Coder 480B A35B?

Meta: Llama 4 Scout offers a 0% read discount ($0.1/1M), whereas Qwen: Qwen3 Coder 480B A35B provides a 66.67% read discount ($0.1/1M). High cache hit ratios (>70%) significantly compress the cost delta in agentic and RAG architectures.

3Can I use Batch API with Meta: Llama 4 Scout or Qwen: Qwen3 Coder 480B A35B to save 50%?

Meta: Llama 4 Scout does not have a native 50% batch endpoint. Qwen: Qwen3 Coder 480B A35B supports 50% batch discounts.

4What are the context window limits and tiered pricing rules for Meta: Llama 4 Scout vs Qwen: Qwen3 Coder 480B A35B?

Meta: Llama 4 Scout features a 1,310.72k context window with flat per-token pricing. In comparison, Qwen: Qwen3 Coder 480B A35B supports 262.144k tokens with flat per-token pricing.