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Comparisons

Kimi K2.7 Code vs OpenAI GPT-OSS 20B

On provider list prices, OpenAI GPT-OSS 20B costs $0.05 per million input tokens against $0.95 for Kimi K2.7 Code: 19.0x apart. Output is $0.20 against $4 (20.0x). On Allocate both bill at list plus the 7% transaction fee.

Kimi K2.7 Code OpenAI GPT-OSS 20B
LabMoonshot AIOpenAI
AccessOpen weightsOpen weights
Context window256K tokens128K tokens
List price, input$0.95 / M tokens$0.05 / M tokens
List price, output$4 / M tokens$0.2 / M tokens
Cached input$0.19 / M tokensn/a
LicenseNot listedApache 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 $2,540 on Kimi K2.7 Code at list: a gap of $2,410, or 19.5x.

Kimi K2.7 Code 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
Kimi K2.7 Code$0.95$4
InputOutput

Choose Kimi K2.7 Code for

  • The longer context window (256K vs 128K tokens)
  • Published cached-input pricing ($0.19 per M tokens)
Kimi K2.7 Code details

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

Common questions

Which is cheaper, Kimi K2.7 Code or OpenAI GPT-OSS 20B?

OpenAI GPT-OSS 20B, on this workload shape. At list prices it is $0.05/$0.20 per million tokens in and out against $0.95/$4 for Kimi K2.7 Code. Billed on Allocate: $0.053/$0.21 against $1.02/$4.28, list plus 7%.

Which has the bigger context window?

Kimi K2.7 Code: 262,144 tokens (256K) against 131,072 (128K) for OpenAI GPT-OSS 20B.

Can I fine-tune Kimi K2.7 Code or OpenAI GPT-OSS 20B?

Both publish open weights (Kimi K2.7 Code: Not listed; OpenAI GPT-OSS 20B: Apache 2.0), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

Related comparisons

Kimi K2.7 Code vs OpenAI GPT-OSS 120BOpenAI GPT-OSS 20B vs OpenAI GPT-OSS 120BKimi K2.7 Code vs GPT-5.5OpenAI GPT-OSS 20B vs GPT-5.5Kimi K2.7 Code vs GLM 4.7 FP8OpenAI GPT-OSS 20B vs GLM 4.7 FP8

Run the numbers on your workload

LLM price comparisonAgent cost calculatorKimi K2.7 CodeOpenAI GPT-OSS 20B

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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