Model comparison
Claude Fable 5 vs DeepSeek V4 Pro
Head-to-head evidence from 5 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Fable 5 #3 (Supported); DeepSeek V4 Pro #48 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Fable 5 and DeepSeek V4 Pro share 5 comparable benchmark results. 2 of 8 categories are comparable. 29 results are unique to Claude Fable 5; 18 to DeepSeek V4 Pro.
Updated July 24, 2026- Shared results
- 5
- Claude Fable 5 only
- 29
- DeepSeek V4 Pro only
- 18
- Comparable categories
- 2 / 8
Pick Claude Fable 5 if you want the stronger benchmark profile. DeepSeek V4 Pro only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 3 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Claude Fable 5 is clearly ahead on the BenchAlign aggregate, 82.76 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Fable 5's sharpest advantage is in agentic, where it averages 84.6 against 59.1. The single biggest benchmark swing on the page is SWE-bench Pro, 80% to 52.1%.
Claude Fable 5 is also the more expensive model on tokens at $10.00 input / $50.00 output per 1M tokens, versus $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro. That is roughly 57.5x on output cost alone. Claude Fable 5 is the reasoning model in the pair, while DeepSeek V4 Pro is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Claude Fable 5 gives you the larger context window at 1M+, compared with 1M for DeepSeek V4 Pro.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Claude Fable 5 | Δ | DeepSeek V4 Pro |
|---|---|---|---|
| Agentic | Claude Fable 584.6 | Margin← 25.5 | DeepSeek V4 Pro59.1 |
| Coding | Claude Fable 589.2 | Margin← 23.9 | DeepSeek V4 Pro65.3 |
| Knowledge | Claude Fable 5Not measured | MarginNo overlap | DeepSeek V4 Pro41.3 |
| Math | Claude Fable 5Not measured | MarginNo overlap | DeepSeek V4 Pro31.7 |
| Multimodal | Claude Fable 557.9 | MarginNo overlap | DeepSeek V4 ProNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Pro
CodingA 80%B 52.1%Winner: Claude Fable 5Δ 27.9SWE-bench Pro: Claude Fable 5 scored 80%; DeepSeek V4 Pro scored 52.1%. Claude Fable 5 wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 84.3%B 59.1%Winner: Claude Fable 5Δ 25.2Terminal-Bench 2.0: Claude Fable 5 scored 84.3%; DeepSeek V4 Pro scored 59.1%. Claude Fable 5 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 95%B 73.6%Winner: Claude Fable 5Δ 21.4SWE-bench Verified: Claude Fable 5 scored 95%; DeepSeek V4 Pro scored 73.6%. Claude Fable 5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Fable 5 | DeepSeek V4 Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Fable 5$10 input / $50 output | DeepSeek V4 Pro$0.435 input / $0.87 output | DeepSeek V4 Pro has the lower combined listed price. |
| Generation speedtokens per second | Claude Fable 5Not available | DeepSeek V4 ProNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Fable 5Not available | DeepSeek V4 ProNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Fable 51M+ | DeepSeek V4 Pro1M | Claude Fable 5 lists the larger context window. |
Benchmark Deep Dive
AgenticClaude Fable 5 wins18 benchmarks
| Benchmark | Claude Fable 5 | DeepSeek V4 Pro | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 84.3% | 59.1% | Claude Fable 5 leads |
| OSWorld-VerifiedSource | 85% | — | Not comparable |
| GDPval-AASource | 1747 | — | Not comparable |
| AA Agentic IndexSource | 52.8% | — | Not comparable |
| τ²-bench resultsSource | 98.5% | — | Not comparable |
| GDPval-AASource | 62.3% | — | Not comparable |
| AA BriefcaseSource | 1574 | — | Not comparable |
| AA AutomationBenchSource | 48.6% | — | Not comparable |
| AA EnterpriseOps-GymSource | 51.1% | — | Not comparable |
| AA Harvey LABSource | 93.6% | — | Not comparable |
| AA Tau3 BankingSource | 26.8% | — | Not comparable |
| terminalBenchHardSource | 62.9% | — | Not comparable |
| aaTerminalBench21Source | 84.6% | — | Not comparable |
| MCP AtlasSource | — | 69.4% | Not comparable |
| ToolathlonSource | — | 46.3% | Not comparable |
| Claw-EvalSource | — | 59.8% | Not comparable |
| Gert LabsSource | — | 50.28% | Not comparable |
| ResearchClawBenchSource | — | 17.1% | Not comparable |
CodingClaude Fable 5 wins10 benchmarks
| Benchmark | Claude Fable 5 | DeepSeek V4 Pro | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 95% | 73.6% | Claude Fable 5 leads |
| SWE-bench ProSource | 80% | 52.1% | Claude Fable 5 leads |
| FrontierCode 1.1 MainSource | 53.5% | — | Not comparable |
| Terminal-Bench 2.0Source | 84.3% | 59.1% | Claude Fable 5 leads |
| cursorBench31Source | 70.6% | — | Not comparable |
| cursorBench32Source | 70.5% | — | Not comparable |
| VulcanBench v3Source | 87.0% | — | Not comparable |
| AA Coding IndexSource | 76.5% | — | Not comparable |
| AA-SciCodeSource | 60.2% | — | Not comparable |
| SWE MultilingualSource | — | 69.8% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | Claude Fable 5 | DeepSeek V4 Pro | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 59.9% | — | Not comparable |
| AA-GPQA DiamondSource | 92.6% | — | Not comparable |
| AA-HLESource | 53.3% | — | Not comparable |
| AA-Omniscience IndexSource | 40.2% | — | Not comparable |
| AA-Omniscience AccuracySource | 61.4% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 54.9% | — | Not comparable |
| MMLU-ProSource | — | 82.9% | Not comparable |
| SimpleQASource | — | 45% | Not comparable |
| Chinese-SimpleQASource | — | 75.8% | Not comparable |
| GPQASource | — | 72.9% | Not comparable |
| GPQA-DSource | — | 72.9% | Not comparable |
| HLESource | — | 7.7% | Not comparable |
Math4 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Fable 5 | DeepSeek V4 Pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 63.5% | — | Not comparable |
Frequently Asked Questions (3)
Which is better, Claude Fable 5 or DeepSeek V4 Pro?
Claude Fable 5 is ahead on BenchLM's BenchAlign leaderboard, 82.76 to 60. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 80% and 52.1%.
Which is better for coding, Claude Fable 5 or DeepSeek V4 Pro?
Claude Fable 5 has the edge for coding in this comparison, averaging 89.2 versus 65.3. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Claude Fable 5 or DeepSeek V4 Pro?
Claude Fable 5 has the edge for agentic tasks in this comparison, averaging 84.6 versus 59.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.