DeepSeek: DeepSeek V3.2 Exp vs Meta: Llama 3.3 70B Instruct
Head-to-head API pricing and cost comparison between DeepSeek’s DeepSeek: DeepSeek V3.2 Exp and Meta’s Meta: Llama 3.3 70B Instruct. Prices auto-refresh daily from OpenRouter.
Meta: Llama 3.3 70B Instruct is 56% cheaper for input tokens; Meta: Llama 3.3 70B Instruct also wins on output tokens.
Side-by-side comparison
| Spec | DeepSeek: DeepSeek V3.2 Exp | Meta: Llama 3.3 70B Instruct |
|---|---|---|
| Input price (per 1M) | $0.27 | $0.12 |
| Cached input (per 1M) | — | — |
| Output price (per 1M) | $0.41 | $0.38 |
| Batch input (per 1M) | — | — |
| Batch output (per 1M) | — | — |
| Reasoning price (per 1M) | — | — |
| Context window | 164K | 131K |
| Vision support | No | No |
| Caching support | No | No |
| Batch API | No | No |
| Reasoning capability | No | No |
Monthly cost at volume
Estimated monthly API spend at common production traffic levels (input/output tokens per request shown).
| Volume | DeepSeek: DeepSeek V3.2 Exp | Meta: Llama 3.3 70B Instruct | Savings |
|---|---|---|---|
1K req/day 500in / 200out tokens | $6.51 | $4.08 | $2.43 Meta: Llama 3.3 70B Instruct wins |
10K req/day 1500in / 500out tokens | $183.00 | $111.00 | $72.00 Meta: Llama 3.3 70B Instruct wins |
100K req/day 3000in / 800out tokens | $3,414 | $1,992 | $1,422 Meta: Llama 3.3 70B Instruct wins |
1M req/day 8000in / 2000out tokens | $89,400 | $51,600 | $37,800 Meta: Llama 3.3 70B Instruct wins |
Adjust input/output token counts, request volume, batch & cached pricing.
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Frequently asked questions
Which is cheaper, DeepSeek: DeepSeek V3.2 Exp or Meta: Llama 3.3 70B Instruct?
For input tokens, Meta: Llama 3.3 70B Instruct is roughly 56% cheaper at $0.12/1M vs $0.27/1M. For output tokens, Meta: Llama 3.3 70B Instruct wins at $0.38/1M. Real-world cost depends on your input/output ratio — use the calculator to model your actual workload.
What’s the context window difference?
DeepSeek: DeepSeek V3.2 Exp has a context window of 164K tokens. Meta: Llama 3.3 70B Instruct offers 131K tokens. Larger context windows are valuable for long documents, RAG pipelines, and multi-turn conversations — but they come with higher input-token bills if you fill them every request.
Should I use DeepSeek: DeepSeek V3.2 Exp or Meta: Llama 3.3 70B Instruct?
Choose DeepSeek: DeepSeek V3.2 Exp if you’re already on the DeepSeek stack, want broad ecosystem support, or prefer its feature set. Choose Meta: Llama 3.3 70B Instruct for Meta’s ecosystem, or its cheaper input tokens. Run a small benchmark on your own prompts before committing — price is only one axis.
How are these prices kept current?
Prices are pulled directly from OpenRouter’s public models API once every 24 hours via a Convex cron job, then normalized to per-1M-token figures. Last refresh: Apr 21, 2026.