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gpt-oss-120b vs Meta Llama3 1 405b Instruct

This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.

Openai

Model

gpt-oss-120b

Tool calling

Context window

131K

131,072 tokens · ~98K words

Model page
Meta

Model

Meta Llama3 1 405b Instruct

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page

Context window · side by side

Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.

gpt-oss-120b131K
Meta Llama3 1 405b Instruct128K

gpt-oss-120b has about 1× the context window of the other in this pair.

gpt-oss-120b has 2% more context capacity (131K vs 128K tokens). gpt-oss-120b is 99% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use gpt-oss-120b. Its 131K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use gpt-oss-120b. Input tokens are 99% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use gpt-oss-120b. Its 131K max output lets you generate complete artifacts in one request.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

Specgpt-oss-120bMeta Llama3 1 405b Instruct
Context window131,072 tokens (131K)128,000 tokens (128K)
Max output tokens131,072 tokens (131K)4,096 tokens (4K)
Speed tierBalancedDeep
VisionNoNo
Function callingYesYes
Extended thinkingYesNo
Prompt cachingYesNo
Batch APINoNo
Release dateAug 2025N/A

Pricing matrix

Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.

Providergpt-oss-120b ingpt-oss-120b outMeta Llama3 1 405b Instruct inMeta Llama3 1 405b Instruct out
Aws Bedrock$5.32/M$16.00/M
Azure$0.150/M$0.600/M
Baseten$0.100/M$0.500/M
Cerebras$0.350/M$0.750/M
Deepinfra$0.050/M$0.450/M
Fireworks$0.150/M$0.600/M
Groq$0.150/M$0.600/M
Ibm Watsonx$0.150/M$0.600/M
Novita$0.050/M$0.250/M
Openrouter$0.180/M$0.800/M
Ovhcloud$0.080/M$0.400/M
Replicate$0.180/M$0.720/M
Sambanova$3.00/M$4.50/M
Together Ai$0.150/M$0.600/M

Frequently asked questions

gpt-oss-120b has a larger context window: 131K tokens vs 128K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

Powered by Mem0

Use a smaller model.
Get better results.

Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model