Qwen3 Max vs Kimi K2 Thinking vs Claude Haiku 4.5
Too close to call on our weighted score (Claude Haiku 4.5 58, Kimi K2 Thinking 58, Qwen3 Max 50). The right pick depends on what you value most.
Alibaba (Qwen)
Qwen3 Max
50/100- ECI142.4
- Price$1.20 / $6.00
- Context262K
Moonshot AI
Kimi K2 Thinking
58/100- ECI146.0
- Price$0.60 / $2.50
- Context262K
Anthropic
Claude Haiku 4.5
58/100- ECI142.4
- Price$1.00 / $5.00
- Context200K
Too close to call
It is close. Our weighted score puts them within a point (Claude Haiku 4.5 58/100, Kimi K2 Thinking 58/100, Qwen3 Max 50/100), so choose by what matters most for your work: Kimi K2 Thinking for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityKimi K2 ThinkingCapabilities Index (ECI): Kimi K2 Thinking 146.0 · Claude Haiku 4.5 142.4 · Qwen3 Max 142.4
- Lowest priceKimi K2 ThinkingKimi K2 Thinking $1.07 · Claude Haiku 4.5 $2.00 · Qwen3 Max $2.40 per 1M tokens (3:1 blend)
- Longest contextQwen3 Max and Kimi K2 ThinkingQwen3 Max 262,144 · Kimi K2 Thinking 262,144 · Claude Haiku 4.5 200,000 tokens
- Widest inputsClaude Haiku 4.5Qwen3 Max: Text · Kimi K2 Thinking: Text · Claude Haiku 4.5: Text, Images, PDFs
- Self-hostingKimi K2 ThinkingPublishes downloadable weights
| Measure | Weight | Qwen3 Max | Kimi K2 Thinking | Claude Haiku 4.5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 68 | 73 | 69 |
| Price | 25% | 32 | 48 | 36 |
| Inputs & features | 15% | 25 | 35 | 80 |
| Context window | 10% | 37 | 37 | 32 |
| Overall | 100% | 50/100 | 58/100 | 58/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 142.4 | 146.0 (best) | 142.4 |
| ECI rank | #91 of 148 | #72 of 148 (best) | #90 of 148 |
| GPQA DiamondGraduate-level science questions | 72.6% | 84.2% (best) | 71.2% |
| FrontierMath Tiers 1–3Research-level mathematics | 19.0% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 73.3% | 83.1% (best) | 66.7% |
| SimpleQA VerifiedShort factual questions | 48.8% (best) | — | 13.2% |
| Price per million tokens | |||
| Input | $1.20 | $0.60 (best) | $1.00 |
| Output | $6.00 | $2.50 (best) | $5.00 |
| Cached input | — | — | $0.10 |
| Blended (3:1) | $2.40 | $1.07 (best) | $2.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 10 providers | Official Anthropic API |
| Limits | |||
| Context window | 262,144 tokens (best) | 262,144 tokens (best) | 200,000 tokens |
| Max output | 65,536 tokens | 262,144 tokens (best) | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | qwen3-max | — | claude-haiku-4-5 |
| API providers | 16 | 10 | 34 (best) |
| Released | Sep 23, 2025 | Nov 6, 2025 | Oct 15, 2025 |
| Knowledge cutoff | Apr 2025 | Aug 2024 | Feb 28, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Qwen3 Max$24.00
Kimi K2 Thinking$11.00
Claude Haiku 4.5$20.00
Which should you choose?
Which is better: Qwen3 Max, Kimi K2 Thinking or Claude Haiku 4.5?
It is close. Our weighted score puts them within a point (Claude Haiku 4.5 58/100, Kimi K2 Thinking 58/100, Qwen3 Max 50/100), so choose by what matters most for your work: Kimi K2 Thinking for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 Max, Kimi K2 Thinking or Claude Haiku 4.5?
Kimi K2 Thinking is cheaper at $0.60 input / $2.50 output per million tokens (median across 10 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 $1.07 per million tokens for Kimi K2 Thinking versus $2.00 for Claude Haiku 4.5 (1.9× as much) and $2.40 for Qwen3 Max (2.2× as much).
Which scores higher on benchmarks?
Kimi K2 Thinking scores higher on the Capabilities Index (ECI): Kimi K2 Thinking 146.0 (#72 of 148), Claude Haiku 4.5 142.4 (#90 of 148) and Qwen3 Max 142.4 (#91 of 148). The confidence ranges of the top two overlap (143.4–147.6 vs 139.5–144.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Kimi K2 Thinking 84.2%, Qwen3 Max 72.6%, Claude Haiku 4.5 71.2%; OTIS Mock AIME 2024–2025 — Kimi K2 Thinking 83.1%, Qwen3 Max 73.3%, Claude Haiku 4.5 66.7%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 Max, Kimi K2 Thinking and Claude Haiku 4.5 yet, so there is no like-for-like coding score. On overall capability, Kimi K2 Thinking 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 and Kimi K2 Thinking have the largest context windows (262,144 and 262,144 tokens), against 200,000 for Claude Haiku 4.5. Maximum output per response: Qwen3 Max up to 65,536, Kimi K2 Thinking up to 262,144, Claude Haiku 4.5 up to 64,000 tokens.
Which can read images, PDFs, audio or video?
Qwen3 Max accepts text; Kimi K2 Thinking accepts text; Claude Haiku 4.5 accepts text, images and PDFs. Claude Haiku 4.5 handles the widest range of inputs.
Are any of these open source?
Kimi K2 Thinking publishes its weights and can be self-hosted; Qwen3 Max and Claude Haiku 4.5 is proprietary.
Which is newer?
Kimi K2 Thinking is the newest, released Nov 6, 2025. Claude Haiku 4.5 came out Oct 15, 2025; Qwen3 Max came out Sep 23, 2025. Knowledge cutoff: Qwen3 Max Apr 2025, Kimi K2 Thinking Aug 2024, Claude Haiku 4.5 Feb 28, 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.