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Llama 4 Scout vs Qwen3 235B A22B Instruct 2507 FP8 Throughput

On provider list prices, Llama 4 Scout costs $0.18 per million input tokens against $0.20 for Qwen3 235B A22B Instruct 2507 FP8 Throughput: 1.1x apart. Output is $0.59 against $0.60. On Allocate both bill at list plus the 7% transaction fee.

Llama 4 Scout Qwen3 235B A22B Instruct 2507 FP8 Throughput
LabMetaQwen
AccessOpen weightsOpen weights
Context window1M tokens256K tokens
List price, input$0.18 / M tokens$0.2 / M tokens
List price, output$0.59 / M tokens$0.6 / M tokens
Cached inputn/an/a
LicenseLlama communityApache 2.0
Fine-tunableYesYes

Specifications and provider list prices from the Allocate catalog, checked 2026-07-08. Billed price is list plus the 7% transaction fee.

What the numbers say

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $422.50 a month on Llama 4 Scout and $450 on Qwen3 235B A22B Instruct 2507 FP8 Throughput at list: a gap of $27.50.

Llama 4 Scout reads 1M tokens per request against 256K for Qwen3 235B A22B Instruct 2507 FP8 Throughput, 4.0x the window. That decides which one can take whole documents without splitting them.

Llama 4 Scout$0.18$0.59
Qwen3 235B A22B Instruct 2507 FP8 Throughput$0.20$0.60
InputOutput

Choose Llama 4 Scout for

  • Whole-document reasoning
  • High-volume extraction
  • Fine-tuning under the Llama 4 license
Llama 4 Scout details

Choose Qwen3 235B A22B Instruct 2507 FP8 Throughput for

  • Fine-tuning under a permissive license (Apache 2.0)
Qwen3 235B A22B Instruct 2507 FP8 Throughput details

Common questions

Which is cheaper, Llama 4 Scout or Qwen3 235B A22B Instruct 2507 FP8 Throughput?

Llama 4 Scout, on this workload shape. At list prices it is $0.18/$0.59 per million tokens in and out against $0.20/$0.60 for Qwen3 235B A22B Instruct 2507 FP8 Throughput. Billed on Allocate: $0.19/$0.63 against $0.21/$0.64, list plus 7%.

Which has the bigger context window?

Llama 4 Scout: 1,048,576 tokens (1M) against 262,144 (256K) for Qwen3 235B A22B Instruct 2507 FP8 Throughput.

Can I fine-tune Llama 4 Scout or Qwen3 235B A22B Instruct 2507 FP8 Throughput?

Both publish open weights (Llama 4 Scout: Llama community; Qwen3 235B A22B Instruct 2507 FP8 Throughput: Apache 2.0), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

Related comparisons

Llama 4 Scout vs Qwen3-VL-8B-InstructQwen3 235B A22B Instruct 2507 FP8 Throughput vs Qwen3-VL-8B-InstructLlama 4 Scout vs Qwen2.5 7B Instruct TurboLlama 4 Scout vs Meta Llama 3.3 70B Instruct TurboQwen3 235B A22B Instruct 2507 FP8 Throughput vs Meta Llama 3.3 70B Instruct TurboLlama 4 Scout vs Qwen3.5 397B A17b

Run the numbers on your workload

LLM price comparisonAgent cost calculatorLlama 4 ScoutQwen3 235B A22B Instruct 2507 FP8 Throughput

Or don’t choose. On Allocate a route name is the contract: point yours at one model today, swap to the other tomorrow, and compare them on your live traffic with per-token metering.

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