Qwen3 32B vs Claude Haiku 4.5 vs DeepSeek-R1
Claude Haiku 4.5 comes out ahead, 58 to 51 and 51 on our weighted score, though DeepSeek-R1 is 41% cheaper per token.
Alibaba (Qwen)Qwen3 32B
51/100- ECI138.5
- Price$0.70 / $2.80
- Context131K
- Our pick
AnthropicClaude Haiku 4.5
58/100- ECI142.4
- Price$1.00 / $5.00
- Context200K
DeepSeekDeepSeek-R1
51/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
Claude Haiku 4.5 is our pick
Claude Haiku 4.5 is the better all-round choice, scoring 58/100 against DeepSeek-R1 (51) and Qwen3 32B (51). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityClaude Haiku 4.5Capabilities Index (ECI): Claude Haiku 4.5 142.4 · DeepSeek-R1 139.0 · Qwen3 32B 138.5
- Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · Qwen3 32B $1.23 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 4.5Claude Haiku 4.5 200,000 · Qwen3 32B 131,072 · DeepSeek-R1 128,000 tokens
- Widest inputsClaude Haiku 4.5Qwen3 32B: Text · Claude Haiku 4.5: Text, Images, PDFs · DeepSeek-R1: Text
- Self-hostingQwen3 32B and DeepSeek-R1Publishes downloadable weights
| Measure | Weight | Qwen3 32B | Claude Haiku 4.5 | DeepSeek-R1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 69 | 64 |
| Price | 25% | 46 | 36 | 47 |
| Inputs & features | 15% | 35 | 80 | 35 |
| Context window | 10% | 24 | 32 | 24 |
| Overall | 100% | 51/100 | 58/100 | 51/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 32BAlibaba (Qwen) | Claude Haiku 4.5Anthropic | DeepSeek-R1DeepSeek |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 138.5 | 142.4 (best) | 139.0 |
| ECI rank | #106 of 148 | #90 of 148 (best) | #104 of 148 |
| GPQA DiamondGraduate-level science questions | 65.7% | 71.2% | 71.7% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 66.9% (best) | 66.7% | 53.3% |
| SimpleQA VerifiedShort factual questions | — | 13.2% | — |
| Price per million tokens | |||
| Input | $0.70 (best) | $1.00 | $0.70 (best) |
| Output | $2.80 | $5.00 | $2.60 (best) |
| Cached input | — | $0.10 | — |
| Blended (3:1) | $1.23 | $2.00 | $1.18 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Anthropic API | Median of 11 providers |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens (best) | 128,000 tokens |
| Max output | 16,384 tokens | 64,000 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | qwen3-32b | claude-haiku-4-5 | — |
| API providers | 14 | 34 (best) | 12 |
| Released | Apr 29, 2025 | Oct 15, 2025 | Jan 20, 2025 |
| Knowledge cutoff | Apr 2025 | Feb 28, 2025 | Jul 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3 32B$12.60
- Claude Haiku 4.5$20.00
- DeepSeek-R1$12.20
Which should you choose?
Which is better: Qwen3 32B, Claude Haiku 4.5 or DeepSeek-R1?
Claude Haiku 4.5 is the better all-round choice, scoring 58/100 against DeepSeek-R1 (51) and Qwen3 32B (51). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 32B, Claude Haiku 4.5 or DeepSeek-R1?
DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). Qwen3 32B costs $0.70 input / $2.80 output per million tokens (official Alibaba API price); Claude Haiku 4.5 costs $1.00 input / $5.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $1.18 per million tokens for DeepSeek-R1 versus $1.23 for Qwen3 32B (1× as much) and $2.00 for Claude Haiku 4.5 (1.7× as much).
Which scores higher on benchmarks?
Claude Haiku 4.5 scores higher on the Capabilities Index (ECI): Claude Haiku 4.5 142.4 (#90 of 148), DeepSeek-R1 139.0 (#104 of 148) and Qwen3 32B 138.5 (#106 of 148). The confidence ranges of the top two overlap (139.5–144.3 vs 136.2–140.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-R1 71.7%, Claude Haiku 4.5 71.2%, Qwen3 32B 65.7%; OTIS Mock AIME 2024–2025 — Qwen3 32B 66.9%, Claude Haiku 4.5 66.7%, DeepSeek-R1 53.3%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 32B, Claude Haiku 4.5 and DeepSeek-R1 yet, so there is no like-for-like coding score. On overall capability, Claude Haiku 4.5 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 4.5 has the largest context window at 200,000 tokens, against 131,072 for Qwen3 32B and 128,000 for DeepSeek-R1. Maximum output per response: Qwen3 32B up to 16,384, Claude Haiku 4.5 up to 64,000, DeepSeek-R1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen3 32B accepts text; Claude Haiku 4.5 accepts text, images and PDFs; DeepSeek-R1 accepts text. Claude Haiku 4.5 handles the widest range of inputs.
Are any of these open source?
Qwen3 32B and DeepSeek-R1 publishes its weights and can be self-hosted; Claude Haiku 4.5 is proprietary.
Which is newer?
Claude Haiku 4.5 is the newest, released Oct 15, 2025. Qwen3 32B came out Apr 29, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: Qwen3 32B Apr 2025, Claude Haiku 4.5 Feb 28, 2025, DeepSeek-R1 Jul 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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