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OpenAI GPT-OSS 20B vs Qwen3 235B A22B Instruct 2507 FP8 Throughput

On provider list prices, OpenAI GPT-OSS 20B costs $0.05 per million input tokens against $0.20 for Qwen3 235B A22B Instruct 2507 FP8 Throughput: 4.0x apart. Output is $0.20 against $0.60 (3.0x). On Allocate both bill at list plus the 7% transaction fee.

OpenAI GPT-OSS 20B Qwen3 235B A22B Instruct 2507 FP8 Throughput
LabOpenAIQwen
AccessOpen weightsOpen weights
Context window128K tokens256K tokens
List price, input$0.05 / M tokens$0.2 / M tokens
List price, output$0.2 / M tokens$0.6 / M tokens
Cached inputn/an/a
LicenseApache 2.0Apache 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 $130 a month on OpenAI GPT-OSS 20B and $450 on Qwen3 235B A22B Instruct 2507 FP8 Throughput at list: a gap of $320, or 3.5x.

Qwen3 235B A22B Instruct 2507 FP8 Throughput reads 256K tokens per request against 128K for OpenAI GPT-OSS 20B, 2.0x the window. That decides which one can take whole documents without splitting them.

OpenAI GPT-OSS 20B$0.05$0.20
Qwen3 235B A22B Instruct 2507 FP8 Throughput$0.20$0.60
InputOutput

Choose OpenAI GPT-OSS 20B for

  • The lower list price ($0.05 in / $0.20 out per M tokens)
  • Fine-tuning under a permissive license (Apache 2.0)
OpenAI GPT-OSS 20B details

Choose Qwen3 235B A22B Instruct 2507 FP8 Throughput for

  • The longer context window (256K vs 128K tokens)
  • Fine-tuning under a permissive license (Apache 2.0)
Qwen3 235B A22B Instruct 2507 FP8 Throughput details

Common questions

Which is cheaper, OpenAI GPT-OSS 20B or Qwen3 235B A22B Instruct 2507 FP8 Throughput?

OpenAI GPT-OSS 20B, on this workload shape. At list prices it is $0.05/$0.20 per million tokens in and out against $0.20/$0.60 for Qwen3 235B A22B Instruct 2507 FP8 Throughput. Billed on Allocate: $0.053/$0.21 against $0.21/$0.64, list plus 7%.

Which has the bigger context window?

Qwen3 235B A22B Instruct 2507 FP8 Throughput: 262,144 tokens (256K) against 131,072 (128K) for OpenAI GPT-OSS 20B.

Can I fine-tune OpenAI GPT-OSS 20B or Qwen3 235B A22B Instruct 2507 FP8 Throughput?

Both publish open weights (OpenAI GPT-OSS 20B: Apache 2.0; 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

OpenAI GPT-OSS 20B vs OpenAI GPT-OSS 120BQwen3 235B A22B Instruct 2507 FP8 Throughput vs OpenAI GPT-OSS 120BQwen3 235B A22B Instruct 2507 FP8 Throughput vs Qwen3-VL-8B-InstructOpenAI GPT-OSS 20B vs Qwen3.5 397B A17bQwen3 235B A22B Instruct 2507 FP8 Throughput vs Qwen3.5 397B A17bOpenAI GPT-OSS 20B vs Qwen3.7 Max

Run the numbers on your workload

LLM price comparisonAgent cost calculatorOpenAI GPT-OSS 20BQwen3 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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