Claude Fable 5.1 vs DeepSeek V4 Flash Base
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | Claude Fable 5.1 | DeepSeek-V4-Flash-Base |
|---|---|---|
| Developer | Anthropic | DeepSeek |
| Family | Claude 5 1 | Deepseek V4 Flash Base |
| Model | Claude Fable 5.1 | DeepSeek-V4-Flash-Base |
| Version | Claude Fable 5.1 | DeepSeek-V4-Flash-Base |
| Lifecycle | active | active |
| Released | 2026-09-01 | 2026-04-24 |
| Knowledge cutoff | 2026-06-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 1,049K |
| Total parameters | Unknown | 292B |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | Yes |
| API available | Yes | Unknown |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard) | Unknown |
| Capabilities | chat, generation, reasoning, tools | generation |
12 comparable fields · 10 material differences · Pair passes the primary-source comparison gate
Claude Fable 5.1 Capabilities
DeepSeek V4 Flash Base Capabilities
Internal Comparison Graph
Related Comparisons
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|---|---|---|---|
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Claude Fable 5.1Anthropic | vs | Grok 4.6xAI | cross-developer peersimage, text |
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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 DeepSeek V4 Flash Base FAQs
Is Claude Fable 5.1 or DeepSeek V4 Flash Base better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Fable 5.1 and DeepSeek V4 Flash Base, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Fable 5.1 or DeepSeek V4 Flash Base?+
Only Claude Fable 5.1 has a directly sourced input price: $10.00 per million tokens. Only Claude Fable 5.1 has a directly sourced output price: $50.00 per million tokens.
Which has a larger context window, Claude Fable 5.1 or DeepSeek V4 Flash Base?+
DeepSeek V4 Flash Base has the larger sourced context window. Claude Fable 5.1 supports 1,000K and DeepSeek V4 Flash Base supports 1,049K.
Which performs better in benchmarks, Claude Fable 5.1 or DeepSeek V4 Flash Base?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Claude Fable 5.1 or DeepSeek V4 Flash Base be self-hosted?+
DeepSeek V4 Flash Base is the only model in this pair currently marked as self-hostable. Claude Fable 5.1 is not marked open weight; DeepSeek V4 Flash Base is open weight.
Can Claude Fable 5.1 and DeepSeek V4 Flash Base understand images?+
Claude Fable 5.1 is documented with image input; DeepSeek V4 Flash Base is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Fable 5.1 or DeepSeek V4 Flash Base?+
Neither has a larger sourced maximum output. Claude Fable 5.1 is 128K and DeepSeek V4 Flash Base is —.
Do Claude Fable 5.1 and DeepSeek V4 Flash Base support reasoning and tool use?+
Claude Fable 5.1: reasoning, tool calling, and image input. DeepSeek V4 Flash Base: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Fable 5.1 or DeepSeek V4 Flash Base?+
Claude Fable 5.1 has 1 sourced provider route; DeepSeek V4 Flash Base has 0, so Claude Fable 5.1 has broader tracked availability.
Which offers better value, Claude Fable 5.1 or DeepSeek V4 Flash Base?+
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.