ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Claude Fable 5.1 vs GLM-5.3 vs GPT-6 Astra

Too close to call on our weighted score (GPT-6 Astra 68, Claude Fable 5.1 66, GLM-5.3 63). The right pick depends on what you value most.

  1. Anthropic

    Claude Fable 5.1

    Released Sep 1, 2026

    66/100
    • ECI166.4
    • Price$10.00 / $50.00
    • Context1M
  2. Z.ai (Zhipu)

    GLM-5.3

    Released Aug 14, 2026

    63/100
    • ECI156.2
    • Price$1.40 / $4.40
    • Context1M
  3. OpenAI

    GPT-6 Astra

    Released Sep 4, 2026New

    68/100
    • ECI169.1
    • Price$10.00 / $50.00
    • Context1.05M
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (GPT-6 Astra 68/100, Claude Fable 5.1 66/100, GLM-5.3 63/100), so choose by what matters most for your work: GPT-6 Astra for raw capability and GLM-5.3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-6 AstraCapabilities Index (ECI): GPT-6 Astra 169.1 · Claude Fable 5.1 166.4 · GLM-5.3 156.2
  • Lowest priceGLM-5.3GLM-5.3 $2.15 · Claude Fable 5.1 $20.00 · GPT-6 Astra $20.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-6 AstraGPT-6 Astra 1,050,000 · Claude Fable 5.1 1,000,000 · GLM-5.3 1,000,000 tokens
  • Widest inputsClaude Fable 5.1 and GPT-6 AstraClaude Fable 5.1: Text, Images, PDFs · GLM-5.3: Text · GPT-6 Astra: Text, Images, PDFs
  • Self-hostingGLM-5.3Publishes downloadable weights
How the score is built
MeasureWeightClaude Fable 5.1GLM-5.3GPT-6 Astra
CapabilityCapabilities Index (ECI)50%9784100
Price25%0330
Inputs & features15%804580
Context window10%606061
Overall100%66/10063/10068/100
02 — Side by side

Every spec in one table

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

Claude Fable 5.1 vs GLM-5.3 vs GPT-6 Astra specifications side by side
SpecificationClaude Fable 5.1AnthropicGLM-5.3Z.ai (Zhipu)GPT-6 AstraOpenAI
Capability
Capabilities Index (ECI)166.4156.2169.1 (best)
ECI rank#6 of 165#33 of 165#1 of 165 (best)
GPQA DiamondGraduate-level science questions—90.9%95.8% (best)
FrontierMath Tiers 1–3Research-level mathematics90.2%68.8%93.7% (best)
OTIS Mock AIME 2024–2025Competition mathematics100% (best)91.1%100% (best)
SimpleQA VerifiedShort factual questions70.8%41.0%75.6% (best)
Price per million tokens
Input$10.00$1.40 (best)$10.00
Output$50.00$4.40 (best)$50.00
Cached input$0.25 (best)$0.26$1.00
Blended (3:1)$20.00$2.15 (best)$20.00
Long-context rateSame rateSame rateOver 272K: $20.00 / $75.00
Price sourceOfficial Anthropic APIOfficial Z.AI APIOfficial OpenAI API
Limits
Context window1,000,000 tokens1,000,000 tokens1,050,000 tokens (best)
Max output128,000 tokens131,072 tokens (best)128,000 tokens
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsYesNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningYeslow · medium · high · xhigh · maxYeslow · high · maxYeslow · medium · high · xhigh · max
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsProprietaryOpenProprietary
API model IDclaude-fable-5-1glm-5.3gpt-6-astra
API providers3783 (best)37
ReleasedSep 1, 2026Aug 14, 2026Sep 4, 2026
Knowledge cutoffJun 2026—Apr 30, 2026
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 Fable 5.1$200.00
  • GLM-5.3$22.80
  • GPT-6 Astra$200.00
04 — Questions

Which should you choose?

Which is better: Claude Fable 5.1, GLM-5.3 or GPT-6 Astra?

It is close. Our weighted score puts them within 2 points (GPT-6 Astra 68/100, Claude Fable 5.1 66/100, GLM-5.3 63/100), so choose by what matters most for your work: GPT-6 Astra for raw capability and GLM-5.3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Claude Fable 5.1, GLM-5.3 or GPT-6 Astra?

GLM-5.3 is cheaper at $1.40 input / $4.40 output per million tokens (official Z.AI API price). Claude Fable 5.1 costs $10.00 input / $50.00 output per million tokens (official Anthropic API price); GPT-6 Astra costs $10.00 input / $50.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $2.15 per million tokens for GLM-5.3 versus $20.00 for Claude Fable 5.1 (9.3× as much) and $20.00 for GPT-6 Astra (9.3× as much).

Which scores higher on benchmarks?

GPT-6 Astra scores higher on the Capabilities Index (ECI): GPT-6 Astra 169.1 (#1 of 165), Claude Fable 5.1 166.4 (#6 of 165) and GLM-5.3 156.2 (#33 of 165). The confidence ranges of the top two overlap (165.9–174.3 vs 163.6–170.8), so treat the gap as small. On individual benchmarks: FrontierMath Tiers 1–3 — GPT-6 Astra 93.7%, Claude Fable 5.1 90.2%, GLM-5.3 68.8%; OTIS Mock AIME 2024–2025 — Claude Fable 5.1 100%, GPT-6 Astra 100%, GLM-5.3 91.1%; SimpleQA Verified — GPT-6 Astra 75.6%, Claude Fable 5.1 70.8%, GLM-5.3 41.0%.

Which is better for coding?

There are no published SWE-bench Verified results for Claude Fable 5.1, GLM-5.3 and GPT-6 Astra yet, so there is no like-for-like coding score. On overall capability, GPT-6 Astra 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?

GPT-6 Astra has the largest context window at 1,050,000 tokens, against 1,000,000 for Claude Fable 5.1 and 1,000,000 for GLM-5.3. Maximum output per response: Claude Fable 5.1 up to 128,000, GLM-5.3 up to 131,072, GPT-6 Astra up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Claude Fable 5.1 accepts text, images and PDFs; GLM-5.3 accepts text; GPT-6 Astra accepts text, images and PDFs. Claude Fable 5.1 handles the widest range of inputs.

Are any of these open source?

GLM-5.3 publishes its weights and can be self-hosted; Claude Fable 5.1 and GPT-6 Astra is proprietary.

Which is newer?

GPT-6 Astra is the newest, released Sep 4, 2026. Claude Fable 5.1 came out Sep 1, 2026; GLM-5.3 came out Aug 14, 2026. Knowledge cutoff: Claude Fable 5.1 Jun 2026, GPT-6 Astra Apr 30, 2026.

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.