Claude Haiku 4.5 vs Qwen3 Max vs Qwen3 VL 30B A3B Instruct
Qwen3 VL 30B A3B Instruct comes out ahead, 62 to 47 and 30 on our weighted score, and it is the cheaper option too.
Anthropic
Claude Haiku 4.5
47/100- ECI142.2
- Price$1.00 / $5.00
- Context200K
Alibaba (Qwen)
Qwen3 Max
30/100- ECI142.4
- Price$1.20 / $6.00
- Context262K
- Our pick
Alibaba (Qwen)
Qwen3 VL 30B A3B Instruct
62/100- ECI—
- Price$0.15 / $0.60
- Context262K
Qwen3 VL 30B A3B Instruct is our pick
Qwen3 VL 30B A3B Instruct is the better all-round choice, scoring 62/100 against Claude Haiku 4.5 (47) and Qwen3 Max (30). It leads on price. Claude Haiku 4.5 wins on inputs & features. 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 priceQwen3 VL 30B A3B InstructQwen3 VL 30B A3B Instruct $0.263 · Claude Haiku 4.5 $2.00 · Qwen3 Max $2.40 per 1M tokens (3:1 blend)
- Longest contextQwen3 Max and Qwen3 VL 30B A3B InstructQwen3 Max 262,144 · Qwen3 VL 30B A3B Instruct 262,144 · Claude Haiku 4.5 200,000 tokens
- Widest inputsClaude Haiku 4.5 and Qwen3 VL 30B A3B InstructClaude Haiku 4.5: Text, Images, PDFs · Qwen3 Max: Text · Qwen3 VL 30B A3B Instruct: Text, Images, Video
- Self-hostingQwen3 VL 30B A3B InstructPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Claude Haiku 4.5 | Qwen3 Max | Qwen3 VL 30B A3B Instruct |
|---|---|---|---|---|
| Price | 50% | 34 | 30 | 74 |
| Inputs & features | 30% | 80 | 25 | 60 |
| Context window | 20% | 32 | 37 | 37 |
| Overall | 100% | 47/100 | 30/100 | 62/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 142.2 | 142.4 (best) | — |
| ECI rank | #102 of 165 | #101 of 165 (best) | — |
| 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 | $1.20 | $0.15 (best) |
| Output | $5.00 | $6.00 | $0.60 (best) |
| Cached input | $0.10 | — | — |
| Blended (3:1) | $2.00 | $2.40 | $0.263 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Anthropic API | Official Alibaba API | Median of 13 providers |
| Limits | |||
| Context window | 200,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 64,000 tokens | 65,536 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | OpenApache-2.0 |
| API model ID | claude-haiku-4-5 | qwen3-max | — |
| API providers | 48 (best) | 13 | 13 |
| Released | Oct 15, 2025 | Sep 23, 2025 | Oct 4, 2025 |
| Knowledge cutoff | Feb 28, 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
Qwen3 Max$24.00
Qwen3 VL 30B A3B Instruct$2.70
Which should you choose?
Which is better: Claude Haiku 4.5, Qwen3 Max or Qwen3 VL 30B A3B Instruct?
Qwen3 VL 30B A3B Instruct is the better all-round choice, scoring 62/100 against Claude Haiku 4.5 (47) and Qwen3 Max (30). It leads on price. Claude Haiku 4.5 wins on inputs & features. 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, Qwen3 Max or Qwen3 VL 30B A3B Instruct?
Qwen3 VL 30B A3B Instruct is cheaper at $0.15 input / $0.60 output per million tokens (median across 13 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 $0.263 per million tokens for Qwen3 VL 30B A3B Instruct versus $2.00 for Claude Haiku 4.5 (7.6× as much) and $2.40 for Qwen3 Max (9.1× 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 142.2, Qwen3 Max has an ECI of 142.4 and Qwen3 VL 30B A3B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 4.5, Qwen3 Max and Qwen3 VL 30B A3B Instruct 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 and Qwen3 VL 30B A3B Instruct have the largest context windows (262,144 and 262,144 tokens), against 200,000 for Claude Haiku 4.5. Maximum output per response: Claude Haiku 4.5 up to 64,000, Qwen3 Max up to 65,536, Qwen3 VL 30B A3B Instruct up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 4.5 accepts text, images and PDFs; Qwen3 Max accepts text; Qwen3 VL 30B A3B Instruct accepts text, images and video. Claude Haiku 4.5 handles the widest range of inputs.
Are any of these open source?
Qwen3 VL 30B A3B Instruct 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 VL 30B A3B Instruct came out Oct 4, 2025; Qwen3 Max came out Sep 23, 2025. Knowledge cutoff: Claude Haiku 4.5 Feb 28, 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 Nov 2, 2026.