ZMIME
Comparison · 3 models · Updated Nov 2, 2026

GLM-4.5-Air vs Claude Haiku 4.5 vs Seed-OSS-36B-Instruct

Claude Haiku 4.5 comes out ahead, 61 to 40 and 31 on our weighted score, though GLM-4.5-Air is 4.7× cheaper per token.

  1. Z.ai (Zhipu)

    GLM-4.5-Air

    Released Jul 28, 2025

    31/100
    • ECI—
    • Price$0.20 / $1.10
    • Context131K
  2. Our pick

    Anthropic

    Claude Haiku 4.5

    Released Oct 15, 2025

    61/100
    • ECI142.2
    • Price$1.00 / $5.00
    • Context200K
  3. ByteDance Seed

    Seed-OSS-36B-Instruct

    Released Aug 20, 2025

    40/100
    • ECI—
    • Price—
    • Context524K
01 — Verdict

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 GLM-4.5-Air (31). 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 priceGLM-4.5-AirGLM-4.5-Air $0.425 · 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 · GLM-4.5-Air 131,072 tokens
  • Widest inputsClaude Haiku 4.5GLM-4.5-Air: Text · Claude Haiku 4.5: Text, Images, PDFs · Seed-OSS-36B-Instruct: Text
  • Self-hostingGLM-4.5-Air and Seed-OSS-36B-InstructPublishes downloadable weights (Apache 2.0)
How the score is built
MeasureWeightGLM-4.5-AirClaude Haiku 4.5Seed-OSS-36B-Instruct
Inputs & features60%358035
Context window40%253249
Overall100%31/10061/10040/100

Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

GLM-4.5-Air vs Claude Haiku 4.5 vs Seed-OSS-36B-Instruct specifications side by side
SpecificationGLM-4.5-AirZ.ai (Zhipu)Claude Haiku 4.5AnthropicSeed-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$0.20 (best)$1.00—
Output$1.10 (best)$5.00—
Cached input$0.03 (best)$0.10—
Blended (3:1)$0.425 (best)$2.00—
Long-context rateSame rateSame rate—
Price sourceOfficial Z.AI APIOfficial Anthropic API—
Limits
Context window131,072 tokens200,000 tokens524,288 tokens (best)
Max output98,304 tokens64,000 tokens524,288 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenProprietaryOpenApache 2.0
API model IDglm-4.5-airclaude-haiku-4-5—
API providers1948 (best)—
ReleasedJul 28, 2025Oct 15, 2025Aug 20, 2025
Knowledge cutoffApr 2025Feb 28, 2025Jul 2024
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • GLM-4.5-Air$4.20
  • Claude Haiku 4.5$20.00
  • Seed-OSS-36B-Instruct—
04 — Questions

Which should you choose?

Which is better: GLM-4.5-Air, 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 GLM-4.5-Air (31). 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, GLM-4.5-Air, Claude Haiku 4.5 or Seed-OSS-36B-Instruct?

GLM-4.5-Air is cheaper at $0.20 input / $1.10 output per million tokens (official Z.AI 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 $0.425 per million tokens for GLM-4.5-Air versus $2.00 for Claude Haiku 4.5 (4.7× 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. GLM-4.5-Air 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 GLM-4.5-Air, 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. All three support tool calling for agent workflows.

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 GLM-4.5-Air. Maximum output per response: GLM-4.5-Air up to 98,304, 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?

GLM-4.5-Air 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?

GLM-4.5-Air and Seed-OSS-36B-Instruct publishes its weights (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; GLM-4.5-Air came out Jul 28, 2025. Knowledge cutoff: GLM-4.5-Air Apr 2025, 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.