Claude Fable 5 vs DeepSeek V4.1 Flash

At a Glance

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Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5#2 of 4695.6 score · 3/3 sources · completeUnrankedNot in the 46-model eligible cohort
CostLower is better · Published-token output estimate#44 of 44$1.01 per LiveBench case#5 of 44$0.022 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5#29 of 3847.8 score · 3/3 sources · completeUnrankedNot in the 38-model eligible cohort
Pricing and Limits
Input priceFrom · USD / 1M tokens$10.00Anthropic · Sep 3, 2026$0.15DeepSeek · Sep 10, 2026
Output priceFrom · USD / 1M tokens$50.00Anthropic · Sep 3, 2026$0.60Deepinfra · Sep 22, 2026
Context windowMaximum documented tokens1,000K1,049K
Model facts checkedAug 28, 2026View model evidence →Sep 10, 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

All benchmark results →
BenchmarkClaude Fable 5DeepSeek-V4.1-Flash
LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader8.81100% of row best · score · Claude Fable 5 (High); 95% CI [7.56791873, 10.05963763]; sessions 38293; observations 2061291; rank 54.8896% of row best · score · Deepseek V4.1 Flash (Max); 95% CI [3.54852933, 6.21109128]; sessions 20080; observations 2295632; rank 12
LiveBench2026-06-25 · overall · leader86.55100% of row best · percent · claude-fable-5-max-effort · 20,255 output tokens / case83.2096% of row best · percent · deepseek-v4.1-flash-max · 36,355 output tokens / case
ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified89.06100% of row best · points · Claude Fable 5 (xhigh) · 18,129 output tokens / case88.0399% of row best · points · DeepSeek V4.1 Flash (max) · 18,199 output tokens / case
Overall ResultCounted from the protocol-matched rows above2 benchmark winsOverall lead0 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

FieldClaude Fable 5DeepSeek-V4.1-Flash
DeveloperAnthropicDeepSeek
FamilyClaude 5Deepseek V4 1
ModelClaude Fable 5DeepSeek-V4.1-Flash
VersionClaude Fable 5DeepSeek-V4.1-Flash
Lifecycleactiveactive
Released2026-06-092026-09-10
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image
Output modalitiesTextText
Context window1,000K1,049K
Total parametersUnknown763.2B
Active parametersUnknownUnknown
LicenseUnknownmit
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessAnthropic (Standard), Deepinfra (Standard), Openrouter (Standard)DeepSeek (Standard), Deepinfra (Standard), Together Ai (Standard)
Capabilitieschat, generation, reasoning, toolsagents, chat, fim, generation, reasoning, responses, structured_outputs, tools, vision
Architecture designUnknownCausal Encoder-Decoder (20 encoder + 20 decoder layers)
Backbone parametersUnknown552000000000 parameters
Active parameters during decodeUnknown16000000000 parameters
Active parameters during prefillUnknown8000000000 parameters
Pre-training corpusUnknown45000000000000 tokens
Reasoning effort rangeUnknown1–100
Routed experts per MoE layerUnknown384 experts
Routed experts per tokenUnknown6 experts
Transformer layersUnknown40 layers

Claude Fable 5 Capabilities

chatgenerationreasoningtools
Serving providers3
Canonical IDanthropic/claude-fable-5

DeepSeek V4.1 Flash Capabilities

agentschatfimgenerationreasoningresponsesstructured outputstoolsvision
Serving providers3
Canonical IDdeepseek-ai/DeepSeek-V4.1-Flash

Primary Evidence

Sources and Freshness

Questions

Claude Fable 5 vs DeepSeek V4.1 Flash FAQs

Is Claude Fable 5 or DeepSeek V4.1 Flash better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Claude Fable 5 and DeepSeek V4.1 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Claude Fable 5 or DeepSeek V4.1 Flash?+

Claude Fable 5 is $10.00 and DeepSeek V4.1 Flash is $0.15 per million tokens, so DeepSeek V4.1 Flash is cheaper on this metric. Claude Fable 5 is $50.00 and DeepSeek V4.1 Flash is $0.60 per million tokens, so DeepSeek V4.1 Flash is cheaper on this metric.

Which has a larger context window, Claude Fable 5 or DeepSeek V4.1 Flash?+

DeepSeek V4.1 Flash has the larger sourced context window. Claude Fable 5 supports 1,000K and DeepSeek V4.1 Flash supports 1,049K.

Which performs better in benchmarks, Claude Fable 5 or DeepSeek V4.1 Flash?+

Claude Fable 5 leads the current overall benchmark count. The result uses 2 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.

Can Claude Fable 5 or DeepSeek V4.1 Flash be self-hosted?+

DeepSeek V4.1 Flash is the only model in this pair currently marked as self-hostable. Claude Fable 5 is not marked open weight; DeepSeek V4.1 Flash is open weight.

Can Claude Fable 5 and DeepSeek V4.1 Flash understand images?+

Claude Fable 5 is documented with image input; DeepSeek V4.1 Flash is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Claude Fable 5 or DeepSeek V4.1 Flash?+

DeepSeek V4.1 Flash has the larger sourced maximum output: Claude Fable 5 supports 128K and DeepSeek V4.1 Flash supports 393K output tokens.

Do Claude Fable 5 and DeepSeek V4.1 Flash support reasoning and tool use?+

Claude Fable 5: reasoning, tool calling, and image input. DeepSeek V4.1 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Claude Fable 5 or DeepSeek V4.1 Flash?+

Claude Fable 5 has 3 sourced provider routes; DeepSeek V4.1 Flash has 3, a tie.

Which offers better value, Claude Fable 5 or DeepSeek V4.1 Flash?+

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.

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