Llama-3.1-70B-Instruct vs Claude Haiku 3.5
Claude Haiku 3.5 comes out ahead, 49 to 40 on our weighted score.
MetaLlama-3.1-70B-Instruct
40/100- ECI125.9
- Price$0.72 / $0.72
- Context128K
- Our pick
AnthropicClaude Haiku 3.5
49/100- ECI127.2
- Price—
- Context200K
Add a model
Make it a three-way comparison.
Claude Haiku 3.5 is our pick
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Llama-3.1-70B-Instruct (40). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityClaude Haiku 3.5Capabilities Index (ECI): Claude Haiku 3.5 127.2 · Llama-3.1-70B-Instruct 125.9
- Lowest priceLlama-3.1-70B-InstructLlama-3.1-70B-Instruct $0.72 per 1M tokens (3:1 blend) · Claude Haiku 3.5 unpriced
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Llama-3.1-70B-Instruct 128,000 tokens
- Widest inputsClaude Haiku 3.5Llama-3.1-70B-Instruct: Text · Claude Haiku 3.5: Text, Images, PDFs
- Self-hostingLlama-3.1-70B-InstructPublishes downloadable weights
| Measure | Weight | Llama-3.1-70B-Instruct | Claude Haiku 3.5 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 48 | 49 |
| Inputs & features | 20% | 25 | 60 |
| Context window | 13% | 24 | 32 |
| Overall | 100% | 40/100 | 49/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Llama-3.1-70B-InstructMeta | Claude Haiku 3.5Anthropic |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 125.9 | 127.2 (best) |
| ECI rank | #136 of 148 | #134 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 44.2% (best) | 38.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 3.6% | 4.3% (best) |
| Price per million tokens | ||
| Input | $0.72 | — |
| Output | $0.72 | — |
| Cached input | — | — |
| Blended (3:1) | $0.72 | — |
| Long-context rate | Same rate | — |
| Price source | Median of 5 providers | — |
| Limits | ||
| Context window | 128,000 tokens | 200,000 tokens (best) |
| Max output | 4,096 tokens | 8,192 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | — | — |
| API providers | 5 | — |
| Released | Jul 23, 2024 | Oct 22, 2024 |
| Knowledge cutoff | Dec 2023 | Jul 31, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Llama-3.1-70B-Instruct$8.64
- Claude Haiku 3.5—
Which should you choose?
Which is better: Llama-3.1-70B-Instruct or Claude Haiku 3.5?
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Llama-3.1-70B-Instruct (40). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Llama-3.1-70B-Instruct or Claude Haiku 3.5?
Llama-3.1-70B-Instruct is cheaper at $0.72 input / $0.72 output per million tokens (median across 5 API providers). . At a typical mix of three input tokens to one output token, that is $0.72 per million tokens for Llama-3.1-70B-Instruct versus . Claude Haiku 3.5 has no published per-token price.
Which scores higher on benchmarks?
Claude Haiku 3.5 scores higher on the Capabilities Index (ECI): Claude Haiku 3.5 127.2 (#134 of 148) and Llama-3.1-70B-Instruct 125.9 (#136 of 148). The confidence ranges of the top two overlap (120.7–129.7 vs 121.0–128.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.1-70B-Instruct 44.2%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Claude Haiku 3.5 4.3%, Llama-3.1-70B-Instruct 3.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.1-70B-Instruct and Claude Haiku 3.5 yet, so there is no like-for-like coding score. On overall capability, Claude Haiku 3.5 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Claude Haiku 3.5 has the largest context window at 200,000 tokens, against 128,000 for Llama-3.1-70B-Instruct. Maximum output per response: Llama-3.1-70B-Instruct up to 4,096, Claude Haiku 3.5 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.1-70B-Instruct accepts text; Claude Haiku 3.5 accepts text, images and PDFs. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Llama-3.1-70B-Instruct publishes its weights and can be self-hosted; Claude Haiku 3.5 is proprietary.
Which is newer?
Claude Haiku 3.5 is the newest, released Oct 22, 2024. Llama-3.1-70B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.1-70B-Instruct Dec 2023, Claude Haiku 3.5 Jul 31, 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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