GPT-OSS 120B vs Llama 3.3 70B: API Price & Benchmark Comparison (INR)
Side-by-side pricing
| GPT-OSS 120B | Llama 3.3 70B | |
|---|---|---|
| Input price / 1M tokens | ₹3.82 | ₹13.41 |
| Output price / 1M tokens | ₹17.54 | ₹41.27 |
| Context window | 131,072 | 131,072 |
| Provider | OpenAI | Meta |
Velona effective INR prices, refreshed every 6 hours (last: 2026-07-28T17:32:59Z).
When to pick which
Both are open-weight workhorses at commodity prices. GPT-OSS 120B is around 3x cheaper on input ($0.036 vs $0.10 per million) and cheaper on output ($0.18 vs $0.32), and being a sparse MoE it also reasons somewhat better on maths and code. Llama 3.3 70B counters with a much larger fine-tuning ecosystem, predictable dense-model behaviour, and years of community prompts and guardrails built around it. For raw cheap inference, GPT-OSS 120B wins on price and reasoning. For workloads that lean on established Llama tooling, fine-tunes, or exact reproducibility, Llama 3.3 remains the safer base.
Benchmarks
GPT-OSS 120B
Benchmarks
Independent scores from Artificial Analysis.
Llama 3.3 70B
No benchmark data.
Cost calculator for both models
Frequently asked questions
Which is cheaper: GPT-OSS 120B or Llama 3.3 70B?
On input tokens, GPT-OSS 120B costs ₹3.82/1M and Llama 3.3 70B costs ₹13.41/1M through Velona. Output tokens: ₹17.54 vs ₹41.27 per 1M.
Can I switch between GPT-OSS 120B and Llama 3.3 70B without changing code?
Yes. Both are behind Velona's single gateway API. Change the model id in your request body and everything else stays the same, including your INR wallet.
Are these prices current?
Prices are regenerated every 6 hours from live provider pricing and the current USD→INR rate, so the figures on this page track what you'd actually be billed.
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