Claude 3.5 Haiku vs Llama 3.1 70B
Side-by-side comparison of Claude 3.5 Haiku (Anthropic) and Llama 3.1 70B (Meta). Exact API pricing per million tokens, context windows, output speed, and total cost on real-world prompts.
Specifications
| Spec | Claude 3.5 Haiku | Llama 3.1 70B |
|---|---|---|
| Provider | Anthropic | Meta |
| Model id | claude-3.5-haiku | llama-3.1-70b |
| Input price (per 1M tokens) | $0.80 | $0.88 |
| Output price (per 1M tokens) | $4.00 | $0.88 |
| Context window | 200,000 | 128,000 |
| Output speed (tokens/sec) | ~120 | ~75 |
Cost on real prompts
Total cost = (input tokens × input price) + (output tokens × output price). Numbers below use the exact pricing tables published by each provider.
| Scenario | Input | Output | Claude 3.5 Haiku | Llama 3.1 70B | Cheaper |
|---|---|---|---|---|---|
| Short question + answer | 50 | 150 | $0.00064 | $0.000176 | Llama 3.1 70B |
| Code review on one file | 500 | 1,500 | $0.006400 | $0.001760 | Llama 3.1 70B |
| Long document summary | 5,000 | 500 | $0.006000 | $0.004840 | Llama 3.1 70B |
| Heavy reasoning task | 2,000 | 8,000 | $0.033600 | $0.008800 | Llama 3.1 70B |
| Full codebase analysis | 50,000 | 10,000 | $0.080000 | $0.052800 | Llama 3.1 70B |
Want the exact cost for your prompt instead of these examples? Open the cost calculator pre-loaded with both models →
When to pick which
Heuristics derived from the spec table above. Always validate on your own prompts before committing — these are starting points, not verdicts.
Pick Claude 3.5 Haiku for
- •tasks needing a larger context window — claude-3.5-haiku fits 2x more tokens than llama-3.1-70b
- •latency-sensitive UX (chat, autocompletion) — claude-3.5-haiku streams faster (~120 vs ~75 tok/s)
Pick Llama 3.1 70B for
- •output-heavy workloads — llama-3.1-70b is meaningfully cheaper per output token
Switching between them
For most use cases, switching providers means updating the model id and the request shape if the providers differ. Within the same provider, it's usually a single-line change.
From Claude 3.5 Haiku to Llama 3.1 70B
# Before
model = "claude-3.5-haiku"
# After
model = "llama-3.1-70b"If the providers differ (Anthropic vs Meta), you'll also need to swap the SDK / endpoint URL. Cross-provider migrations usually take 30 minutes to a few hours depending on how many features (streaming, function calling, tool use) you depend on.
Calculate cost on your own prompt
The examples above use generic input/output ratios. For an exact comparison, paste your real prompt into the calculator — it counts tokens with the right tokenizer for each model and shows side-by-side cost.
Open the calculator with both models →