Claude Haiku 3.5 vs Llama-3.1-70B-Instruct vs Llama-3.3-70B-Instruct
Claude Haiku 3.5 comes out ahead, 49 to 41 and 40 on our weighted score.
- Our pick
AnthropicClaude Haiku 3.5
49/100- ECI127.2
- Price—
- Context200K
MetaLlama-3.1-70B-Instruct
40/100- ECI125.9
- Price$0.72 / $0.72
- Context128K
- Meta
Llama-3.3-70B-Instruct
41/100- ECI127.3
- Price$0.59 / $0.724
- Context128K
Claude Haiku 3.5 is our pick
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Llama-3.3-70B-Instruct (41) and 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%.
- CapabilityLlama-3.3-70B-InstructCapabilities Index (ECI): Llama-3.3-70B-Instruct 127.3 · Claude Haiku 3.5 127.2 · Llama-3.1-70B-Instruct 125.9
- Lowest priceLlama-3.3-70B-InstructLlama-3.3-70B-Instruct $0.624 · Llama-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 · Llama-3.3-70B-Instruct 128,000 tokens
- Widest inputsClaude Haiku 3.5Claude Haiku 3.5: Text, Images, PDFs · Llama-3.1-70B-Instruct: Text · Llama-3.3-70B-Instruct: Text
- Self-hostingLlama-3.1-70B-Instruct and Llama-3.3-70B-InstructPublishes downloadable weights
| Measure | Weight | Claude Haiku 3.5 | Llama-3.1-70B-Instruct | Llama-3.3-70B-Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 49 | 48 | 49 |
| Inputs & features | 20% | 60 | 25 | 25 |
| Context window | 13% | 32 | 24 | 24 |
| Overall | 100% | 49/100 | 40/100 | 41/100 |
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 | Claude Haiku 3.5Anthropic | Llama-3.1-70B-InstructMeta | Llama-3.3-70B-InstructMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 127.2 | 125.9 | 127.3 (best) |
| ECI rank | #134 of 148 | #136 of 148 | #133 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 38.1% | 44.2% | 47.4% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 4.3% | 3.6% | 5.1% (best) |
| Price per million tokens | |||
| Input | — | $0.72 | $0.59 (best) |
| Output | — | $0.72 (best) | $0.724 |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.72 | $0.624 (best) |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 5 providers | Median of 21 providers |
| Limits | |||
| Context window | 200,000 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 8,192 tokens (best) | 4,096 tokens | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | — | — | llama-3.3-70b-instruct |
| API providers | — | 5 | 24 (best) |
| Released | Oct 22, 2024 | Jul 23, 2024 | Dec 6, 2024 |
| Knowledge cutoff | Jul 31, 2024 | Dec 2023 | Dec 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Claude Haiku 3.5—
- Llama-3.1-70B-Instruct$8.64
- Llama-3.3-70B-Instruct$7.35
Which should you choose?
Which is better: Claude Haiku 3.5, Llama-3.1-70B-Instruct or Llama-3.3-70B-Instruct?
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Llama-3.3-70B-Instruct (41) and 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, Claude Haiku 3.5, Llama-3.1-70B-Instruct or Llama-3.3-70B-Instruct?
Llama-3.3-70B-Instruct is cheaper at $0.59 input / $0.724 output per million tokens (median across 21 API providers; free on Llama). Llama-3.1-70B-Instruct costs $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 $0.624 per million tokens for Llama-3.3-70B-Instruct versus $0.72 for Llama-3.1-70B-Instruct (1.2× as much). Claude Haiku 3.5 has no published per-token price.
Which scores higher on benchmarks?
Llama-3.3-70B-Instruct scores higher on the Capabilities Index (ECI): Llama-3.3-70B-Instruct 127.3 (#133 of 148), 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 (122.5–129.5 vs 120.7–129.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.3-70B-Instruct 47.4%, Llama-3.1-70B-Instruct 44.2%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Llama-3.3-70B-Instruct 5.1%, 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 Claude Haiku 3.5, Llama-3.1-70B-Instruct and Llama-3.3-70B-Instruct yet, so there is no like-for-like coding score. On overall capability, Llama-3.3-70B-Instruct leads, which tends to carry over to coding, but test on your own codebase. All three 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 and 128,000 for Llama-3.3-70B-Instruct. Maximum output per response: Claude Haiku 3.5 up to 8,192, Llama-3.1-70B-Instruct up to 4,096, Llama-3.3-70B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 3.5 accepts text, images and PDFs; Llama-3.1-70B-Instruct accepts text; Llama-3.3-70B-Instruct accepts text. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Llama-3.1-70B-Instruct and Llama-3.3-70B-Instruct publishes its weights and can be self-hosted; Claude Haiku 3.5 is proprietary.
Which is newer?
Llama-3.3-70B-Instruct is the newest, released Dec 6, 2024. Claude Haiku 3.5 came out Oct 22, 2024; Llama-3.1-70B-Instruct came out Jul 23, 2024. Knowledge cutoff: Claude Haiku 3.5 Jul 31, 2024, Llama-3.1-70B-Instruct Dec 2023, Llama-3.3-70B-Instruct Dec 2023.
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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