Baichuan M2 32B vs Claude Haiku 4.5 vs Seed-OSS-36B-Instruct
Claude Haiku 4.5 comes out ahead, 61 to 40 and 16 on our weighted score, though Baichuan M2 32B is 29× cheaper per token.
BaichuanBaichuan M2 32B
16/100- ECI—
- Price$0.07 / $0.07
- Context131K
- Our pick
AnthropicClaude Haiku 4.5
61/100- ECI142.2
- Price$1.00 / $5.00
- Context200K
ByteDance SeedSeed-OSS-36B-Instruct
40/100- ECI—
- Price—
- Context524K
Claude Haiku 4.5 is our pick
Claude Haiku 4.5 is the better all-round choice, scoring 61/100 against Seed-OSS-36B-Instruct (40) and Baichuan M2 32B (16). It leads on inputs & features. Seed-OSS-36B-Instruct wins on context window. The score weighs inputs & features 60%, context window 40%. 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 priceBaichuan M2 32BBaichuan M2 32B $0.07 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend) · Seed-OSS-36B-Instruct unpriced
- Longest contextSeed-OSS-36B-InstructSeed-OSS-36B-Instruct 524,288 · Claude Haiku 4.5 200,000 · Baichuan M2 32B 131,072 tokens
- Widest inputsClaude Haiku 4.5Baichuan M2 32B: Text · Claude Haiku 4.5: Text, Images, PDFs · Seed-OSS-36B-Instruct: Text
- Self-hostingBaichuan M2 32B and Seed-OSS-36B-InstructPublishes downloadable weights (Apache-2.0 and Apache 2.0)
| Measure | Weight | Baichuan M2 32B | Claude Haiku 4.5 | Seed-OSS-36B-Instruct |
|---|---|---|---|---|
| Inputs & features | 60% | 10 | 80 | 35 |
| Context window | 40% | 25 | 32 | 49 |
| Overall | 100% | 16/100 | 61/100 | 40/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Baichuan M2 32BBaichuan | Claude Haiku 4.5Anthropic | Seed-OSS-36B-InstructByteDance Seed |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 142.2 | — |
| ECI rank | — | #102 of 165 | — |
| GPQA DiamondGraduate-level science questions | — | 71.2% | 71.5% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 66.7% | 67.5% (best) |
| SimpleQA VerifiedShort factual questions | — | 13.2% | — |
| Price per million tokens | |||
| Input | $0.07 (best) | $1.00 | — |
| Output | $0.07 (best) | $5.00 | — |
| Cached input | — | $0.10 | — |
| Blended (3:1) | $0.07 (best) | $2.00 | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Median of 1 providers | Official Anthropic API | — |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens | 524,288 tokens (best) |
| Max output | 131,072 tokens | 64,000 tokens | 524,288 tokens (best) |
| 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 | No | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | OpenApache 2.0 |
| API model ID | — | claude-haiku-4-5 | — |
| API providers | 1 | 48 (best) | — |
| Released | Aug 13, 2025 | Oct 15, 2025 | Aug 20, 2025 |
| Knowledge cutoff | — | 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.
- Baichuan M2 32B$0.84
- Claude Haiku 4.5$20.00
- Seed-OSS-36B-Instruct—
Which should you choose?
Which is better: Baichuan M2 32B, Claude Haiku 4.5 or Seed-OSS-36B-Instruct?
Claude Haiku 4.5 is the better all-round choice, scoring 61/100 against Seed-OSS-36B-Instruct (40) and Baichuan M2 32B (16). It leads on inputs & features. Seed-OSS-36B-Instruct wins on context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Baichuan M2 32B, Claude Haiku 4.5 or Seed-OSS-36B-Instruct?
Baichuan M2 32B is cheaper at $0.07 input / $0.07 output per million tokens (median across 1 API provider). 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 $0.07 per million tokens for Baichuan M2 32B versus $2.00 for Claude Haiku 4.5 (29× as much). Seed-OSS-36B-Instruct has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Baichuan M2 32B has not been scored yet, Claude Haiku 4.5 has an ECI of 142.2 and Seed-OSS-36B-Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Baichuan M2 32B, Claude Haiku 4.5 and Seed-OSS-36B-Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Baichuan M2 32B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Seed-OSS-36B-Instruct has the largest context window at 524,288 tokens, against 200,000 for Claude Haiku 4.5 and 131,072 for Baichuan M2 32B. Maximum output per response: Baichuan M2 32B up to 131,072, Claude Haiku 4.5 up to 64,000, Seed-OSS-36B-Instruct up to 524,288 tokens.
Which can read images, PDFs, audio or video?
Baichuan M2 32B accepts text; Claude Haiku 4.5 accepts text, images and PDFs; Seed-OSS-36B-Instruct accepts text. Claude Haiku 4.5 handles the widest range of inputs.
Are any of these open source?
Baichuan M2 32B and Seed-OSS-36B-Instruct publishes its weights (Apache-2.0 and Apache 2.0) 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. Seed-OSS-36B-Instruct came out Aug 20, 2025; Baichuan M2 32B came out Aug 13, 2025. Knowledge cutoff: Claude Haiku 4.5 Feb 28, 2025, Seed-OSS-36B-Instruct 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 Nov 2, 2026.
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