ZMIME
Comparison · 3 models · Updated Nov 2, 2026

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

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

  1. 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
  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. 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
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. Claude Haiku 4.5 wins on inputs & features. GLM-4.7 wins on capability. 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 4.5Claude Haiku 4.5: Text, Images, PDFs · GPT OSS 20B: Text · GLM-4.7: Text
  • Self-hostingGPT OSS 20B and GLM-4.7Publishes downloadable weights
How the score is built
MeasureWeightClaude Haiku 4.5GPT OSS 20BGLM-4.7
CapabilityCapabilities Index (ECI)50%676169
Price25%349048
Inputs & features15%803535
Context window10%322532
Overall100%57/10061/10055/100
02 — Side by side

Every spec in one table

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

Claude Haiku 4.5 vs GPT OSS 20B vs GLM-4.7 specifications side by side
SpecificationClaude Haiku 4.5AnthropicGPT OSS 20BOpenAIGLM-4.7Z.ai (Zhipu)
Capability
Capabilities Index (ECI)142.2137.8143.7 (best)
ECI rank#102 of 165#122 of 165#94 of 165 (best)
GPQA DiamondGraduate-level science questions71.2%60.8%83.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics66.7%65.3%83.3% (best)
SimpleQA VerifiedShort factual questions13.2%—32.2% (best)
Price per million tokens
Input$1.00$0.07 (best)$0.60
Output$5.00$0.25 (best)$2.20
Cached input$0.10 (best)—$0.11
Blended (3:1)$2.00$0.115 (best)$1.00
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Anthropic APIMedian of 37 providersOfficial Z.AI API
Limits
Context window200,000 tokens131,072 tokens204,800 tokens (best)
Max output64,000 tokens32,768 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsYesNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsProprietaryOpenOpen
API model IDclaude-haiku-4-5—glm-4.7
API providers48 (best)4131
ReleasedOct 15, 2025Aug 5, 2025Dec 22, 2025
Knowledge cutoffFeb 28, 2025Jun 2024Apr 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.

  • Claude Haiku 4.5$20.00
  • GPT OSS 20B$1.20
  • GLM-4.7$10.40
04 — Questions

Which should you choose?

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

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. Claude Haiku 4.5 wins on inputs & features. GLM-4.7 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

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

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 Claude Haiku 4.5, GPT OSS 20B and GLM-4.7 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: Claude Haiku 4.5 up to 64,000, GPT OSS 20B up to 32,768, GLM-4.7 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Claude Haiku 4.5 accepts text, images and PDFs; GPT OSS 20B accepts text; GLM-4.7 accepts text. Claude Haiku 4.5 handles the widest range of inputs.

Are any of these open source?

GPT OSS 20B and GLM-4.7 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: Claude Haiku 4.5 Feb 28, 2025, GPT OSS 20B Jun 2024, GLM-4.7 Apr 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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