Claude Haiku 3.5 vs Llama-3.3-70B-Instruct vs Qwen3 Max
Qwen3 Max comes out ahead, 55 to 49 and 41 on our weighted score, though Llama-3.3-70B-Instruct is 3.8× cheaper per token.
AnthropicClaude Haiku 3.5
49/100- ECI127.2
- Price—
- Context200K
MetaLlama-3.3-70B-Instruct
41/100- ECI127.3
- Price$0.59 / $0.724
- Context128K
- Our pick
Alibaba (Qwen)Qwen3 Max
55/100- ECI142.4
- Price$1.20 / $6.00
- Context262K
Qwen3 Max is our pick
Qwen3 Max is the better all-round choice, scoring 55/100 against Claude Haiku 3.5 (49) and Llama-3.3-70B-Instruct (41). It leads on capability and context window. Claude Haiku 3.5 wins on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityQwen3 MaxCapabilities Index (ECI): Qwen3 Max 142.4 · Llama-3.3-70B-Instruct 127.3 · Claude Haiku 3.5 127.2
- Lowest priceLlama-3.3-70B-InstructLlama-3.3-70B-Instruct $0.624 · Qwen3 Max $2.40 per 1M tokens (3:1 blend) · Claude Haiku 3.5 unpriced
- Longest contextQwen3 MaxQwen3 Max 262,144 · Claude Haiku 3.5 200,000 · Llama-3.3-70B-Instruct 128,000 tokens
- Widest inputsClaude Haiku 3.5Claude Haiku 3.5: Text, Images, PDFs · Llama-3.3-70B-Instruct: Text · Qwen3 Max: Text
- Self-hostingLlama-3.3-70B-InstructPublishes downloadable weights
| Measure | Weight | Claude Haiku 3.5 | Llama-3.3-70B-Instruct | Qwen3 Max |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 49 | 49 | 68 |
| Inputs & features | 20% | 60 | 25 | 25 |
| Context window | 13% | 32 | 24 | 37 |
| Overall | 100% | 49/100 | 41/100 | 55/100 |
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-3.3-70B-InstructMeta | Qwen3 MaxAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 127.2 | 127.3 | 142.4 (best) |
| ECI rank | #134 of 148 | #133 of 148 | #91 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 38.1% | 47.4% | 72.6% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 19.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 4.3% | 5.1% | 73.3% (best) |
| SimpleQA VerifiedShort factual questions | — | — | 48.8% |
| Price per million tokens | |||
| Input | — | $0.59 (best) | $1.20 |
| Output | — | $0.724 (best) | $6.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.624 (best) | $2.40 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 21 providers | Official Alibaba API |
| Limits | |||
| Context window | 200,000 tokens | 128,000 tokens | 262,144 tokens (best) |
| Max output | 8,192 tokens | 4,096 tokens | 65,536 tokens (best) |
| 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 | Proprietary |
| API model ID | — | llama-3.3-70b-instruct | qwen3-max |
| API providers | — | 24 (best) | 16 |
| Released | Oct 22, 2024 | Dec 6, 2024 | Sep 23, 2025 |
| Knowledge cutoff | Jul 31, 2024 | Dec 2023 | Apr 2025 |
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-3.3-70B-Instruct$7.35
- Qwen3 Max$24.00
Which should you choose?
Which is better: Claude Haiku 3.5, Llama-3.3-70B-Instruct or Qwen3 Max?
Qwen3 Max is the better all-round choice, scoring 55/100 against Claude Haiku 3.5 (49) and Llama-3.3-70B-Instruct (41). It leads on capability and context window. Claude Haiku 3.5 wins on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Claude Haiku 3.5, Llama-3.3-70B-Instruct or Qwen3 Max?
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). Qwen3 Max costs $1.20 input / $6.00 output per million tokens (official Alibaba API price). 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 $2.40 for Qwen3 Max (3.8× as much). Claude Haiku 3.5 has no published per-token price.
Which scores higher on benchmarks?
Qwen3 Max scores higher on the Capabilities Index (ECI): Qwen3 Max 142.4 (#91 of 148), Llama-3.3-70B-Instruct 127.3 (#133 of 148) and Claude Haiku 3.5 127.2 (#134 of 148). Their confidence ranges do not overlap (140.0–144.6 vs 122.5–129.5), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen3 Max 72.6%, Llama-3.3-70B-Instruct 47.4%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Qwen3 Max 73.3%, Llama-3.3-70B-Instruct 5.1%, Claude Haiku 3.5 4.3%.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 3.5, Llama-3.3-70B-Instruct and Qwen3 Max yet, so there is no like-for-like coding score. On overall capability, Qwen3 Max 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?
Qwen3 Max has the largest context window at 262,144 tokens, against 200,000 for Claude Haiku 3.5 and 128,000 for Llama-3.3-70B-Instruct. Maximum output per response: Claude Haiku 3.5 up to 8,192, Llama-3.3-70B-Instruct up to 4,096, Qwen3 Max up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 3.5 accepts text, images and PDFs; Llama-3.3-70B-Instruct accepts text; Qwen3 Max accepts text. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Llama-3.3-70B-Instruct publishes its weights and can be self-hosted; Claude Haiku 3.5 and Qwen3 Max is proprietary.
Which is newer?
Qwen3 Max is the newest, released Sep 23, 2025. Llama-3.3-70B-Instruct came out Dec 6, 2024; Claude Haiku 3.5 came out Oct 22, 2024. Knowledge cutoff: Claude Haiku 3.5 Jul 31, 2024, Llama-3.3-70B-Instruct Dec 2023, Qwen3 Max Apr 2025.
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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