Anthropic: Claude Haiku 4.5 vs Meta: Llama 3.1 70B Instruct
Head-to-head API pricing and cost comparison between Anthropic’s Anthropic: Claude Haiku 4.5 and Meta’s Meta: Llama 3.1 70B Instruct. Prices auto-refresh daily from OpenRouter.
Meta: Llama 3.1 70B Instruct is 28% cheaper for input tokens; Meta: Llama 3.1 70B Instruct also wins on output tokens.
Side-by-side comparison
| Spec | Anthropic: Claude Haiku 4.5 | Meta: Llama 3.1 70B Instruct |
|---|---|---|
| Input price (per 1M) | $1.00 | $0.72 |
| Cached input (per 1M) | $0.10 | — |
| Output price (per 1M) | $5.00 | $0.72 |
| Batch input (per 1M) | $0.50 | — |
| Batch output (per 1M) | $2.50 | — |
| Reasoning price (per 1M) | — | — |
| Context window | 200K | 131K |
| Vision support | Yes | No |
| Caching support | Yes | No |
| Batch API | Yes | 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 | Anthropic: Claude Haiku 4.5 | Meta: Llama 3.1 70B Instruct | Savings |
|---|---|---|---|
1K req/day 500in / 200out tokens | $45.00 | $15.12 | $29.88 Meta: Llama 3.1 70B Instruct wins |
10K req/day 1500in / 500out tokens | $1,200 | $432.00 | $768.00 Meta: Llama 3.1 70B Instruct wins |
100K req/day 3000in / 800out tokens | $21,000 | $8,208 | $12,792 Meta: Llama 3.1 70B Instruct wins |
1M req/day 8000in / 2000out tokens | $540,000 | $216,000 | $324,000 Meta: Llama 3.1 70B Instruct wins |
Adjust input/output token counts, request volume, batch & cached pricing.
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Frequently asked questions
Which is cheaper, Anthropic: Claude Haiku 4.5 or Meta: Llama 3.1 70B Instruct?
For input tokens, Meta: Llama 3.1 70B Instruct is roughly 28% cheaper at $0.72/1M vs $1.00/1M. For output tokens, Meta: Llama 3.1 70B Instruct wins at $0.72/1M. Real-world cost depends on your input/output ratio — use the calculator to model your actual workload.
What’s the context window difference?
Anthropic: Claude Haiku 4.5 has a context window of 200K tokens. Meta: Llama 3.1 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 Anthropic: Claude Haiku 4.5 or Meta: Llama 3.1 70B Instruct?
Choose Anthropic: Claude Haiku 4.5 if you’re already on the Anthropic stack, want broad ecosystem support, or prefer its feature set. Choose Meta: Llama 3.1 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: Nov 8, 2026.