Llama 3.1 8B Instruct vs gpt-oss-120b

Practical read: Llama 3.1 8B Instruct costs about a third as much and starts answering sooner. One API key runs both.

No card required. Start with 1 million free tokens.

Side by side:

Meta: Llama 3.1 8B Instruct compared with OpenAI: gpt-oss-120b
Attribute	Llama 3.1 8B Instruct `meta-llama/llama-3.1-8b-instruct`	gpt-oss-120b `openai/gpt-oss-120b`
Price, 1M in + out	$0.074 Novita AI, cheapest route	$0.21 Weights & Biases, cheapest route
Best for	Low cost and speed
Input / output, 1M	$0.021 / $0.053	$0.032 / $0.18
Cached input	Not published	$0.015825/1M to $0.1055/1M
Context window	131K 131,072 tokens	131K 131,072 tokens
First token, p50	0.23 s via Weights & Biases	0.48 s via Cerebras
AI IQ	Unrated	IQ 98 #136 on AI IQ
Provider routes	3 with failover	24 with failover
Privacy	Varies by provider	Confidential E2EE and zero retention route
Recent route uptime range	100.00%	100.00%
Publisher	Meta	OpenAI
Modes	chat	chat
More detail	Overview Pricing Providers	Overview Pricing Providers

Price adds one million input and one million output tokens on the cheapest route. Prices and speed change: see the monthly reports and run a small eval before you choose a default.

Test both with your agent

Paste this into Claude Code, Cursor or any coding agent.

Compare Llama 3.1 8B Instruct and gpt-oss-120b in this project through TrustedRouter.

1. Read https://trustedrouter.com/docs/llms.txt
2. Point the OpenAI-compatible client at
   https://api.trustedrouter.com/v1 and read the key from
   TRUSTEDROUTER_API_KEY.
3. Run our eval prompts on meta-llama/llama-3.1-8b-instruct, then on openai/gpt-oss-120b.
4. Show me cost, latency and quality side by side before changing the default.

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.trustedrouter.com/v1",
    api_key=os.environ["TRUSTEDROUTER_API_KEY"],
)
for model in ("meta-llama/llama-3.1-8b-instruct", "openai/gpt-oss-120b"):
    response = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": "What is the capital of France?"}],
    )
    print(model, response.choices[0].message.content)

for model in meta-llama/llama-3.1-8b-instruct openai/gpt-oss-120b; do
  curl https://api.trustedrouter.com/v1/chat/completions \
    -H "Authorization: Bearer $TRUSTEDROUTER_API_KEY" \
    -H "Content-Type: application/json" \
    -d "{\"model\": \"$model\", \"messages\": [{\"role\": \"user\", \"content\": \"What is the capital of France?\"}]}"
done

Your agent will need an API key.

Questions

Which should I use, Meta: Llama 3.1 8B Instruct or OpenAI: gpt-oss-120b?

Meta: Llama 3.1 8B Instruct has the lower published input-plus-output rate and the lower measured p50 time to first token. gpt-oss-120b has more Credits provider routes. Their context windows are the same size.

Is Meta: Llama 3.1 8B Instruct or OpenAI: gpt-oss-120b cheaper?

The current cheapest TrustedRouter route is $0.07385/1M for Meta: Llama 3.1 8B Instruct and $0.211/1M for OpenAI: gpt-oss-120b. The comparison uses current catalog prices and updates as provider pricing changes.

Is Meta: Llama 3.1 8B Instruct or OpenAI: gpt-oss-120b faster?

Current measured p50 time to first token is 235 ms for Meta: Llama 3.1 8B Instruct and 482 ms for OpenAI: gpt-oss-120b. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Meta: Llama 3.1 8B Instruct and OpenAI: gpt-oss-120b with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between meta-llama/llama-3.1-8b-instruct and openai/gpt-oss-120b. This makes side-by-side evals possible without maintaining two provider integrations.

More comparisons

All comparisons

Try Llama 3.1 8B Instruct and gpt-oss-120b with one key.

TrustedRouter is useful when you know the model you want, but still need provider rollover, budget limits, usage records, and a prompt path you can verify.

No card required. Start with 1 million free tokens.