Claude Fable 5 vs GLM 5.3
At a Glance
| Compare | Claude Fable 5Anthropic |  GLM 5.3Z.ai |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #2 of 4695.6 score · 3/3 sources · complete | #16 of 4670.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 46.9–80.3 |
| CostLower is better · Published-token output estimate | #44 of 44$1.01 per LiveBench case | #34 of 44$0.248 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | #29 of 3847.8 score · 3/3 sources · complete | #26 of 3850.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 38.2–54.9 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $10.00Anthropic ↗ · Sep 3, 2026 | $1.20Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $50.00Anthropic ↗ · Sep 3, 2026 | $4.00Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1,000K | 1,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 29, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Claude Fable 5 | GLM-5.3 |
|---|---|---|
| LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader | 8.81100% of row best · score · Claude Fable 5 (High); 95% CI [7.56791873, 10.05963763]; sessions 38293; observations 2061291; rank 5 | 3.0595% of row best · score · GLM 5.3 (Max); 95% CI [2.43618871, 3.66634458]; sessions 73287; observations 6652488; rank 18 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,492.63100% of row best · rating · claude-fable-5; 95% CI [1487.86770992, 1497.38399139]; votes 30057; rank 7 | 1,475.0899% of row best · rating · glm-5.3-max; 95% CI [1468.67816284, 1481.48915679]; votes 10960; rank 20 |
| LiveBench2026-06-25 · overall · leader | 86.55100% of row best · percent · claude-fable-5-max-effort · 20,255 output tokens / case | 79.1591% of row best · percent · glm-5.3 · 62,090 output tokens / case |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 89.06100% of row best · points · Claude Fable 5 (xhigh) · 18,129 output tokens / case | 88.3499% of row best · points · GLM-5.3 · 22,204 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 3 benchmark winsOverall lead | 0 benchmark wins |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Claude Fable 5 | GLM-5.3 |
|---|---|---|
| Developer | Anthropic | Z.ai |
| Family | Claude 5 | Glm 5 3 |
| Model | Claude Fable 5 | GLM-5.3 |
| Version | Claude Fable 5 | GLM-5.3 |
| Lifecycle | active | active |
| Released | 2026-06-09 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 1,000K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Anthropic (Standard), Deepinfra (Standard), Openrouter (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard) |
| Capabilities | chat, generation, reasoning, tools | agents, chat, reasoning, structured_outputs, tools |
Claude Fable 5 Capabilities
GLM 5.3 Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
Claude Fable 5Anthropic | vs | GLM-5.2Z.ai | cross-developer peerstext |
Claude Fable 5Anthropic | vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text |
Claude Fable 5Anthropic | vs | Claude Fable 5.1Anthropic | family variantsimage, text |
Claude Fable 5Anthropic | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
Claude Fable 5Anthropic | vs |  DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
Claude Fable 5Anthropic | vs | Grok 4.6xAI | cross-developer peersimage, text |
Claude Fable 5Anthropic | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text |
Claude Fable 5Anthropic | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | Claude Fable 5Anthropic | cross-developer peersimage, text |
Claude Fable 5Anthropic | vs |  Hy4 previewTencent | cross-developer peerstext |
Claude Fable 5Anthropic | vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text |
Claude Fable 5Anthropic | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Claude Fable 5 vs GLM 5.3 FAQs
Is Claude Fable 5 or GLM 5.3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Fable 5 and GLM 5.3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Fable 5 or GLM 5.3?+
Claude Fable 5 is $10.00 and GLM 5.3 is $1.20 per million tokens, so GLM 5.3 is cheaper on this metric. Claude Fable 5 is $50.00 and GLM 5.3 is $4.00 per million tokens, so GLM 5.3 is cheaper on this metric.
Which has a larger context window, Claude Fable 5 or GLM 5.3?+
Neither model has a larger sourced context window in this comparison. Claude Fable 5 is 1,000K and GLM 5.3 is 1,000K.
Which performs better in benchmarks, Claude Fable 5 or GLM 5.3?+
Claude Fable 5 leads the current overall benchmark count. The result uses 3 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.
Can Claude Fable 5 or GLM 5.3 be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Claude Fable 5 is not marked open weight; GLM 5.3 is not marked open weight.
Can Claude Fable 5 and GLM 5.3 understand images?+
Claude Fable 5 is documented with image input; GLM 5.3 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Fable 5 or GLM 5.3?+
GLM 5.3 has the larger sourced maximum output: Claude Fable 5 supports 128K and GLM 5.3 supports 131K output tokens.
Do Claude Fable 5 and GLM 5.3 support reasoning and tool use?+
Claude Fable 5: reasoning, tool calling, and image input. GLM 5.3: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Fable 5 or GLM 5.3?+
Claude Fable 5 has 3 sourced provider routes; GLM 5.3 has 4, so GLM 5.3 has broader tracked availability.
Which offers better value, Claude Fable 5 or GLM 5.3?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.