ZMIME
Comparison · 3 models · Updated Nov 2, 2026

GLM-4.7 vs GPT OSS 20B vs Claude Haiku 4.5

GPT OSS 20B comes out ahead, 61 to 57 and 55 on our weighted score, and it is the cheaper option too.

  1. Z.ai (Zhipu)

    GLM-4.7

    Released Dec 22, 2025

    55/100
    • ECI143.7
    • Price$0.60 / $2.20
    • Context205K
    Full specs Remove GLM-4.7
  2. Our pick

    OpenAI

    GPT OSS 20B

    Released Aug 5, 2025

    61/100
    • ECI137.8
    • Price$0.07 / $0.25
    • Context131K
    Full specs Remove GPT OSS 20B

  3. Anthropic

    Claude Haiku 4.5

    Released Oct 15, 2025

    57/100
    • ECI142.2
    • Price$1.00 / $5.00
    • Context200K
    Full specs Remove Claude Haiku 4.5
01 — Verdict

GPT OSS 20B is our pick

GPT OSS 20B is the better all-round choice, scoring 61/100 against Claude Haiku 4.5 (57) and GLM-4.7 (55). It leads on price. GLM-4.7 wins on capability. Claude Haiku 4.5 wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGLM-4.7Capabilities Index (ECI): GLM-4.7 143.7 · Claude Haiku 4.5 142.2 · GPT OSS 20B 137.8
  • Lowest priceGPT OSS 20BGPT OSS 20B $0.115 · GLM-4.7 $1.00 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
  • Longest contextGLM-4.7GLM-4.7 204,800 · Claude Haiku 4.5 200,000 · GPT OSS 20B 131,072 tokens
  • Widest inputsClaude Haiku 4.5GLM-4.7: Text · GPT OSS 20B: Text · Claude Haiku 4.5: Text, Images, PDFs
  • Self-hostingGLM-4.7 and GPT OSS 20BPublishes downloadable weights
How the score is built
MeasureWeightGLM-4.7GPT OSS 20BClaude Haiku 4.5
CapabilityCapabilities Index (ECI)50%696167
Price25%489034
Inputs & features15%353580
Context window10%322532
Overall100%55/10061/10057/100
02 — Side by side

Every spec in one table

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

GLM-4.7 vs GPT OSS 20B vs Claude Haiku 4.5 specifications side by side
SpecificationGLM-4.7Z.ai (Zhipu)GPT OSS 20BOpenAIClaude Haiku 4.5Anthropic
Capability
Capabilities Index (ECI)143.7 (best)137.8142.2
ECI rank#94 of 165 (best)#122 of 165#102 of 165
GPQA DiamondGraduate-level science questions83.3% (best)60.8%71.2%
OTIS Mock AIME 2024–2025Competition mathematics83.3% (best)65.3%66.7%
SimpleQA VerifiedShort factual questions32.2% (best)—13.2%
Price per million tokens
Input$0.60$0.07 (best)$1.00
Output$2.20$0.25 (best)$5.00
Cached input$0.11—$0.10 (best)
Blended (3:1)$1.00$0.115 (best)$2.00
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Z.AI APIMedian of 37 providersOfficial Anthropic API
Limits
Context window204,800 tokens (best)131,072 tokens200,000 tokens
Max output131,072 tokens (best)32,768 tokens64,000 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenProprietary
API model IDglm-4.7—claude-haiku-4-5
API providers314148 (best)
ReleasedDec 22, 2025Aug 5, 2025Oct 15, 2025
Knowledge cutoffApr 2025Jun 2024Feb 28, 2025
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-4.7$10.40
  • GPT OSS 20B$1.20
  • Claude Haiku 4.5$20.00
04 — Questions

Which should you choose?

Which is better: GLM-4.7, GPT OSS 20B or Claude Haiku 4.5?

GPT OSS 20B is the better all-round choice, scoring 61/100 against Claude Haiku 4.5 (57) and GLM-4.7 (55). It leads on price. GLM-4.7 wins on capability. Claude Haiku 4.5 wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GLM-4.7, GPT OSS 20B or Claude Haiku 4.5?

GPT OSS 20B is cheaper at $0.07 input / $0.25 output per million tokens (median across 37 API providers). GLM-4.7 costs $0.60 input / $2.20 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 $0.115 per million tokens for GPT OSS 20B versus $1.00 for GLM-4.7 (8.7× as much) and $2.00 for Claude Haiku 4.5 (17× as much).

Which scores higher on benchmarks?

GLM-4.7 scores higher on the Capabilities Index (ECI): GLM-4.7 143.7 (#94 of 165), Claude Haiku 4.5 142.2 (#102 of 165) and GPT OSS 20B 137.8 (#122 of 165). The confidence ranges of the top two overlap (141.4–145.8 vs 139.4–143.9), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-4.7 83.3%, Claude Haiku 4.5 71.2%, GPT OSS 20B 60.8%; OTIS Mock AIME 2024–2025 — GLM-4.7 83.3%, Claude Haiku 4.5 66.7%, GPT OSS 20B 65.3%.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-4.7, GPT OSS 20B and Claude Haiku 4.5 yet, so there is no like-for-like coding score. On overall capability, GLM-4.7 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?

GLM-4.7 has the largest context window at 204,800 tokens, against 200,000 for Claude Haiku 4.5 and 131,072 for GPT OSS 20B. Maximum output per response: GLM-4.7 up to 131,072, GPT OSS 20B up to 32,768, Claude Haiku 4.5 up to 64,000 tokens.

Which can read images, PDFs, audio or video?

GLM-4.7 accepts text; GPT OSS 20B 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?

GLM-4.7 and GPT OSS 20B publishes its weights and can be self-hosted; Claude Haiku 4.5 is proprietary.

Which is newer?

GLM-4.7 is the newest, released Dec 22, 2025. Claude Haiku 4.5 came out Oct 15, 2025; GPT OSS 20B came out Aug 5, 2025. Knowledge cutoff: GLM-4.7 Apr 2025, GPT OSS 20B Jun 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 Nov 2, 2026.

05 — Keep comparing

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