Claude Fable 5.1 vs Hy3
At a Glance
| Compare | Claude Fable 5.1Anthropic |  Hy3Tencent |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #1 of 4699.0 score · 3/3 sources · complete | UnrankedNot in the 46-model eligible cohort |
| CostLower is better · Published-token output estimate | #43 of 44$0.824 per LiveBench case | UnrankedNot in the 44-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.5 | #22 of 3851.7 score · 3/3 sources · complete | UnrankedNot in the 38-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $10.00Anthropic ↗ · Sep 3, 2026 | $0.13Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $50.00Anthropic ↗ · Sep 3, 2026 | $0.528Openrouter ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1,000K | 262K |
| Model facts checked | Sep 2, 2026View model evidence → | Aug 28, 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 5.1 | Hy3 |
|---|---|---|
| LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader | 13.71100% of row best · score · Claude Fable 5.1 (Max); 95% CI [11.98654915, 15.42403622]; sessions 13320; observations 1453463; rank 1 | -5.2383% of row best · score · Hy3; 95% CI [-6.39472360, -4.07137134]; sessions 27371; observations 992576; rank 35 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,507.58100% of row best · rating · claude-fable-5.1-max; 95% CI [1499.42882565, 1515.73467375]; votes 5783; rank 1 | 1,440.5896% of row best · rating · hy3; 95% CI [1433.39024152, 1447.77894384]; votes 8047; rank 65 |
| Overall ResultCounted from the protocol-matched rows above | 2 benchmark winsNo overall winner | 0 benchmark winsNo overall winner |
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 5.1 | Hy3 |
|---|---|---|
| Developer | Anthropic | Tencent |
| Family | Claude 5 1 | Hy3 |
| Model | Claude Fable 5.1 | Hy3 |
| Version | Claude Fable 5.1 | Hy3 |
| Lifecycle | active | active |
| Released | 2026-09-01 | Unknown |
| Knowledge cutoff | 2026-06-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 262K |
| Total parameters | Unknown | 298.8B |
| Active parameters | Unknown | 21B |
| License | Unknown | apache-2.0 |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard) | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, tools |
Claude Fable 5.1 Capabilities
Hy3 Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
Claude Fable 5Anthropic | vs | Claude Fable 5.1Anthropic | family variantsimage, text |
Claude Fable 5.1Anthropic | vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
Claude Fable 5.1Anthropic | vs |  DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs | Grok 4.6xAI | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | Claude Fable 5.1Anthropic | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Claude Fable 5.1Anthropic | vs | Hy4 previewTencent | cross-developer peerstext |
Claude Fable 5.1Anthropic | vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Claude Fable 5.1 vs Hy3 FAQs
Is Claude Fable 5.1 or Hy3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Fable 5.1 and Hy3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Fable 5.1 or Hy3?+
Claude Fable 5.1 is $10.00 and Hy3 is $0.13 per million tokens, so Hy3 is cheaper on this metric. Claude Fable 5.1 is $50.00 and Hy3 is $0.528 per million tokens, so Hy3 is cheaper on this metric.
Which has a larger context window, Claude Fable 5.1 or Hy3?+
Claude Fable 5.1 has the larger sourced context window. Claude Fable 5.1 supports 1,000K and Hy3 supports 262K.
Which performs better in benchmarks, Claude Fable 5.1 or Hy3?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Claude Fable 5.1 or Hy3 be self-hosted?+
Hy3 is the only model in this pair currently marked as self-hostable. Claude Fable 5.1 is not marked open weight; Hy3 is open weight.
Can Claude Fable 5.1 and Hy3 understand images?+
Claude Fable 5.1 is documented with image input; Hy3 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Fable 5.1 or Hy3?+
Neither has a larger sourced maximum output. Claude Fable 5.1 is 128K and Hy3 is —.
Do Claude Fable 5.1 and Hy3 support reasoning and tool use?+
Claude Fable 5.1: reasoning, tool calling, and image input. Hy3: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Fable 5.1 or Hy3?+
Claude Fable 5.1 has 1 sourced provider route; Hy3 has 3, so Hy3 has broader tracked availability.
Which offers better value, Claude Fable 5.1 or Hy3?+
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.