Claude Haiku 4.5 vs Apertus 70B vs Qwen3 Max
Claude Haiku 4.5 comes out ahead, 48 to 33 and 31 on our weighted score, though Apertus 70B is 39% cheaper per token.
- Our pick
AnthropicClaude Haiku 4.5
48/100- ECI142.4
- Price$1.00 / $5.00
- Context200K
Swiss AI
Apertus 70B
33/100- ECI—
- Price$0.82 / $2.42
- Context66K
Alibaba (Qwen)Qwen3 Max
31/100- ECI142.4
- Price$1.20 / $6.00
- Context262K
Claude Haiku 4.5 is our pick
Claude Haiku 4.5 is the better all-round choice, scoring 48/100 against Apertus 70B (33) and Qwen3 Max (31). It leads on inputs & features. Apertus 70B wins on price. Qwen3 Max wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceApertus 70BApertus 70B $1.22 · Claude Haiku 4.5 $2.00 · Qwen3 Max $2.40 per 1M tokens (3:1 blend)
- Longest contextQwen3 MaxQwen3 Max 262,144 · Claude Haiku 4.5 200,000 · Apertus 70B 65,536 tokens
- Widest inputsClaude Haiku 4.5Claude Haiku 4.5: Text, Images, PDFs · Apertus 70B: Text · Qwen3 Max: Text
- Self-hostingApertus 70BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Claude Haiku 4.5 | Apertus 70B | Qwen3 Max |
|---|---|---|---|---|
| Price | 50% | 36 | 46 | 32 |
| Inputs & features | 30% | 80 | 25 | 25 |
| Context window | 20% | 32 | 12 | 37 |
| Overall | 100% | 48/100 | 33/100 | 31/100 |
Left out because at least one model lacks the data: capability. 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 4.5Anthropic | Apertus 70BSwiss AI | Qwen3 MaxAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 142.4 (best) | — | 142.4 |
| ECI rank | #90 of 148 (best) | — | #91 of 148 |
| GPQA DiamondGraduate-level science questions | 71.2% | — | 72.6% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 19.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 66.7% | — | 73.3% (best) |
| SimpleQA VerifiedShort factual questions | 13.2% | — | 48.8% (best) |
| Price per million tokens | |||
| Input | $1.00 | $0.82 (best) | $1.20 |
| Output | $5.00 | $2.42 (best) | $6.00 |
| Cached input | $0.10 | — | — |
| Blended (3:1) | $2.00 | $1.22 (best) | $2.40 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Anthropic API | Median of 3 providers | Official Alibaba API |
| Limits | |||
| Context window | 200,000 tokens | 65,536 tokens | 262,144 tokens (best) |
| Max output | 64,000 tokens | 8,192 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 | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | OpenApache-2.0 | Proprietary |
| API model ID | claude-haiku-4-5 | — | qwen3-max |
| API providers | 34 (best) | 3 | 16 |
| Released | Oct 15, 2025 | Sep 2, 2025 | Sep 23, 2025 |
| Knowledge cutoff | Feb 28, 2025 | Sep 2025 | 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 4.5$20.00
- Apertus 70B$13.04
- Qwen3 Max$24.00
Which should you choose?
Which is better: Claude Haiku 4.5, Apertus 70B or Qwen3 Max?
Claude Haiku 4.5 is the better all-round choice, scoring 48/100 against Apertus 70B (33) and Qwen3 Max (31). It leads on inputs & features. Apertus 70B wins on price. Qwen3 Max wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Claude Haiku 4.5, Apertus 70B or Qwen3 Max?
Apertus 70B is cheaper at $0.82 input / $2.42 output per million tokens (median across 3 API providers). Claude Haiku 4.5 costs $1.00 input / $5.00 output per million tokens (official Anthropic API price); 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 $1.22 per million tokens for Apertus 70B versus $2.00 for Claude Haiku 4.5 (1.6× as much) and $2.40 for Qwen3 Max (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Claude Haiku 4.5 has an ECI of 142.4, Apertus 70B has not been scored yet and Qwen3 Max has an ECI of 142.4.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 4.5, Apertus 70B and Qwen3 Max yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. 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 4.5 and 65,536 for Apertus 70B. Maximum output per response: Claude Haiku 4.5 up to 64,000, Apertus 70B up to 8,192, Qwen3 Max up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 4.5 accepts text, images and PDFs; Apertus 70B accepts text; Qwen3 Max accepts text. Claude Haiku 4.5 handles the widest range of inputs.
Are any of these open source?
Apertus 70B publishes its weights (Apache-2.0) and can be self-hosted; Claude Haiku 4.5 and Qwen3 Max is proprietary.
Which is newer?
Claude Haiku 4.5 is the newest, released Oct 15, 2025. Qwen3 Max came out Sep 23, 2025; Apertus 70B came out Sep 2, 2025. Knowledge cutoff: Claude Haiku 4.5 Feb 28, 2025, Apertus 70B Sep 2025, 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.
