MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
中文
Model Comparison · Head to Head

Claude Fable 5.1 vs GLM-5.3-Flash

Claude Fable 5.1 wins on Overall, Coding, Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorAnthropic / Zhipu AI
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose Claude Fable 5.1 when coding depth, long-context reliability matter most; choose GLM-5.3-Flash when lower cost, lower latency, fine-tuning/ecosystem is the priority.

Choose Claude Fable 5.1 if you…

  • Top agentic coding (Terminal-Bench 55.8)
  • Highest AA Intelligence Index
  • Reliable 1M long-running agents
  • Cache reads 75% cheaper
  • Best for: Agentic coding, Long-horizon tasks, Scientific research

Choose GLM-5.3-Flash if you…

  • Among the cheapest
  • Fast
  • Open source
  • Best for: Ultra-fast, Ultra-low-cost, High concurrency
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 26 tracked models.

Claude Fable 5.1 Higher overall
Anthropic · #2 overall
Overall95
Coding99
Multimodal97
VS
GLM-5.3-Flash
Zhipu AI · #21 overall
Overall65
Coding60
Multimodal63

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

Specs & pricing — every field side by side

List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.

DimensionClaude Fable 5.1GLM-5.3-FlashVerdict
VendorAnthropic (US)Zhipu AI (CN)Different vendors
Released2026.092026.08Claude Fable 5.1 is newer
Overall (rank)95 · #265 · #21Claude Fable 5.1 +30
Coding99 · #160 · #24Claude Fable 5.1 +39
Multimodal97 · #163 · #25Claude Fable 5.1 +34
Context window1M128KClaude Fable 5.1 larger
Max output128K64KGLM-5.3-Flash longer
Effective-context9980Claude Fable 5.1 more reliable
Input $/1M$10$0.07GLM-5.3-Flash cheaper
Output $/1M$50$0.25GLM-5.3-Flash cheaper
Cache discount90% offnoneClaude Fable 5.1 deeper
Speed~32 tok/s~90 tok/sGLM-5.3-Flash faster
TTFT1.1s0.2sGLM-5.3-Flash snappier
Function calling9370Claude Fable 5.1 ahead
Refusal rate~9%~6%GLM-5.3-Flash less restrictive
English9965Claude Fable 5.1
Chinese8385GLM-5.3-Flash
Modalitiestext, imagetextdifferent coverage
Open weightsNoYesGLM-5.3-Flash is open
Fine-tuningNoYes
Free tierNo free tier; cache reads cut to a quarter of costChatGLM free
SOC2 / no-trainyes / yesno / yes
Private deploymentNoYesGLM-5.3-Flash

Fields drawn from vendor public documentation and the Modelspectra 26-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

Claude Fable 5.1 leads the overall aggregate by 30 points (95 vs 65). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while GLM-5.3-Flash remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a decisive gap: Claude Fable 5.1 scores 99 against 60. On multi-file edits, SWE-style tickets and long-horizon agent loops Claude Fable 5.1 needs fewer correction turns; GLM-5.3-Flash is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

Claude Fable 5.1 leads multimodal 97 vs 63. A concrete modality difference: Claude Fable 5.1 additionally handles image. Neither emits native video, so the comparison is about parsing images and documents, not generation.

Speed & latency

GLM-5.3-Flash is faster in interactive use: ~90 tok/s with 0.2s TTFT versus ~32 tok/s with 1.1s TTFT (about 2.8× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.

Context: window vs usable recall

Nominal windows are 1M for Claude Fable 5.1 and 128K for GLM-5.3-Flash. Effective-context scores point the same way as window size — Claude Fable 5.1 is ahead on usable recall (99 vs 80), so prefer it for long-document work where details cannot be missed.

Price & total cost

GLM-5.3-Flash is the cheaper API at $0.07/$0.25 versus Claude Fable 5.1 at $10/$50 per 1M input/output tokens — list input is about 133.3× lower. Cache discounts (Claude Fable 5.1 90%) shift the effective bill, worked out below.

Chinese vs English

English: Claude Fable 5.1 99 vs GLM-5.3-Flash 65. Chinese: 83 vs 85. For Chinese-language production, GLM-5.3-Flash is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: Claude Fable 5.1 93 vs GLM-5.3-Flash 70, so Claude Fable 5.1 has the edge on structured tool use. Fine-tuning is available from GLM-5.3-Flash. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

Cost worked example — same workload, real token math

Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.

Scenario · per monthClaude Fable 5.1GLM-5.3-FlashGap
List priceno cache applied$2,500100M in × $10  +  30M out × $50$15100M in × $0.07  +  30M out × $0.25166.67×gap
With caching90% of inputs cache-hit$1,69090M cached in × $1  +  10M in × $10  +  30M out × $50$15no published cache discount112.67×gap

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose Claude Fable 5.1 (coding 99 vs 60).
IF you serve real-time users and latency is a product KPI  →  choose GLM-5.3-Flash (~90 tok/s, 0.2s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose GLM-5.3-Flash ($$0.07/$$0.25 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose Claude Fable 5.1 (effective context 99 vs 80).
07

Frequently asked questions

Is Claude Fable 5.1 worth the higher price over GLM-5.3-Flash?
At list the input rate is 133.3x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when Claude Fable 5.1's stronger dimensions protect revenue; for routine volume GLM-5.3-Flash is the economical pick.
Which is better for agentic coding?
Claude Fable 5.1 is decisively stronger for coding (99 vs 60 on the aggregate). The gap shows on SWE-style multi-file tasks and long agent loops that need fewer correction turns; GLM-5.3-Flash is fine for routine scripts.
How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, Claude Fable 5.1 is about $1,690/month and GLM-5.3-Flash about $15/month after cache discounts ($2,500 and $15 at list).
Does the bigger context window actually matter?
Nominal windows are Claude Fable 5.1 (1M) and GLM-5.3-Flash (128K), but usable recall follows the effective-context score (99 vs 80). Prefer the higher effective-context model for long-document work where nothing can be missed.
How do they differ for Chinese-language and data-residency use?
GLM-5.3-Flash is the Chinese model (Chinese score 85, domestic cloud, possible private deployment) while Claude Fable 5.1 is the global model (Chinese 83, overseas API). Pick by language quality, access path and where data must reside.
Can I self-host either model?
GLM-5.3-Flash ships open weights and can be self-hosted (GPU permitting) for data control; Claude Fable 5.1 is a closed managed API with no self-hosting. Choose open weights when residency or cost-at-scale dominates, managed API for convenience.