DeepSeek•Rank #11NEW

DeepSeek-V4.1-Flash-1017

Open Weights • Open Sourcegeneralreasoningcodingagentopen-sourcefast

Leaderboard Score

59.4

Scale: 0 - 100

Throughput Speed

178 tps

Context Window

API Pricing / 1M

Free/Open Source

Parameter Scale

MoE

Monthly API Cost Calculator

DeepSeek-V4.1-Flash-1017 rates: $0.14/1M input • $0.28/1M output. Pick a workload preset or enter your own token volumes.

Monthly input (M tokens)Monthly output (M tokens)

Same workload on published-rate alternatives

DeepSeek-V4-Flash-Max (DeepSeek)

MiMo-V2.5 (Xiaomi)

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Estimates use listed API rates at time of writing; providers may differ in caching discounts, rate limits, and batching pricing.

Sourced AI Radar & Benchmarks•9 Evaluated Metrics

Capability Radar & Benchmark Scores

Multi-Axis Capability Radar

Comparing DeepSeek-V4.1-Flash-1017 against Frontier Top 10 & Open-Source average

0 - 100 Scale

DeepSeek-V4.1-Flash-1017

Frontier Top 10 Avg

Open-Source Avg

Performance Vectors

Where DeepSeek-V4.1-Flash-1017 Leads

Coding & SWETop 10: 80% • OS: 51.1%

82.5%+2.5% vs Top 10

Reasoning & MathTop 10: 89.2% • OS: 52.7%

92.2%+3.0% vs Top 10

Agent & Tool AutomationTop 10: 78.3% • OS: 36.4%

69.3%-9.0% vs Top 10

Terminal & CLI ExecutionTop 10: 66.8% • OS: 46.2%

42.3%-24.5% vs Top 10

MMLU & Knowledge QATop 10: 50% • OS: 86.7%

74.3%+24.3% vs Top 10

Cyber & Security ExploitsTop 10: 86.2% • OS: 81.2%

56.4%-29.8% vs Top 10

All Verified Benchmark Evaluations

Direct Pass@1 and resolution rates across standardized evaluations.

OverallCodingReasoningAgenticTerminal

Featured Compute Platform

Run Benchmarks on Dedicated AI Clusters

Zero-cold-start inference endpoints with dedicated GPU instances.

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Executive Analysis & Verdict

DeepSeek-V4.1-Flash-1017 by DeepSeek is a high-throughput open-weights model scoring 59.4 overall, delivering #1 Global coding accuracy on DeepSWE v1.1 (77.0%) and xdev-bench-hard (85.7%) at a blistering 178 tokens per second.

Key Strengths & Highlights

•#1 Global SOTA in repository code repair on DeepSWE v1.1 (77.0%), outperforming both Claude Opus 5.5 and GPT-6 Astra
•Industry-leading inference efficiency: 178 tokens/second throughput at $0.14 / $0.28 per million tokens
•High-precision open agent automation with 66.6% on AutomationBench-AA and 1746 GDPval-AA Elo
•1,048,576 token native context window with multimodal vision understanding

Limitations & Considerations

•Lower performance on raw interactive CLI tools (42.3 Terminal-Bench 4.0) relative to Kimi K3.1 Pro

Recommended Workflows

High-volume production code review, continuous integration bug-fixing, automated patch generation, scalable agent fleets, and low-latency API workloads

Architectural Overview & Capability Profile

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek as the updated autumn 2026 iteration of the V4.1 MoE architecture. Engineered to maximize developer coding accuracy and inference economy, V4.1 Flash delivers unprecedented price-to-performance efficiency. On the comprehensive RankLLMs composite evaluation index, DeepSeek-V4.1-Flash-1017 captures an overall rating of 59.4 / 100 (Rank #9 Overall).

Operating with open weights and available across global API gateways, DeepSeek-V4.1-Flash-1017 runs at a blistering 178 tokens/second with native 1-million-token context windows.

Benchmark Performance & Real-World Utility

In verified evaluations from the October 2026 frontier benchmarking suites, DeepSeek-V4.1-Flash-1017 demonstrates exceptional strengths in software engineering:

Repository Bug Fixing & Code Generation:
- DeepSWE v1.1 (77.0%): #1 Global Ranking, surpassing Claude Opus 5.5 (74.2%), GPT-6 Astra (74.1%), and Kimi K3.1 Pro (75.5%) in resolving multi-file real-world GitHub issues.
- xdev-bench-hard (85.7%): Sets the global ceiling in complex developer task completion.
- Kimi Code Bench 2.0 (76.1%): Validates high consistency in algorithmic code construction.
Agent Workflows & Reasoning:
- AutomationBench-AA (66.6%): Strong multi-step API integration and workflow orchestration.
- GDPval-AA (1746 Elo) & AA-Briefcase (1570 Elo): Strong peer alignment in enterprise problem solving.
- GPQA-Diamond (92.2%): Reliable scientific and formal domain reasoning.
- BioMysteryBench (80.0%) & BabyVision (92.5%): High-accuracy multimodal vision and biological reasoning.

Inference Latency & Cost Architecture

Token Context Window: 1,048,576 tokens native context window.
Inference Speed: Blistering throughput of 178 tokens/second, offering near-instant streaming for interactive coding tools.
Commercial API Pricing: Market-leading economy at $0.14 per 1M input tokens and $0.28 per 1M output tokens, with cache-hit reads reduced to fractions of a cent ($0.014/1M).

Strengths, Limitations & Ideal Workflows

Primary Strengths

#1 Global SOTA in repository code repair on DeepSWE v1.1 (77.0%)
Industry-leading inference efficiency: 178 tps throughput at $0.14 / $0.28 per 1M tokens
High-precision open agent automation with 66.6% on AutomationBench-AA
1M token context window with multimodal vision understanding

Known Considerations

Lower performance on raw interactive CLI tools (42.3 Terminal-Bench 4.0) relative to Kimi K3.1 Pro.

Recommended Use Cases

High-volume production code review, continuous integration bug-fixing, automated patch generation, scalable agent fleets, and low-latency API workloads.

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Frequently Asked Questions About DeepSeek-V4.1-Flash-1017

What is DeepSeek-V4.1-Flash-1017 and who developed it?↓

DeepSeek-V4.1-Flash-1017 is a open source large language model developed by DeepSeek. It ranks #11 on the RankLLMs composite leaderboard, ahead of 89% of the 95 models we track, with an overall score of 59.4 / 100.

Can DeepSeek-V4.1-Flash-1017 handle very long documents and codebases?↓

DeepSeek-V4.1-Flash-1017 supports a 1.0M-token input context window and generates about 178 tps tokens per second in our reference measurements and which is enough to hold entire repositories, long transcripts, or multi-document research sets in a single session..

Can I self-host DeepSeek-V4.1-Flash-1017?↓

Yes. DeepSeek-V4.1-Flash-1017 is released with Open Source licensing, so it can be self-hosted on private infrastructure with no per-token API cost. Check the specifications above for the memory footprint and quantization headroom to plan your hardware.

What is DeepSeek-V4.1-Flash-1017 best at?↓

DeepSeek-V4.1-Flash-1017 is strongest in #1 Global SOTA in repository code repair on DeepSWE v1.1 (77.0%), outperforming both Claude Opus 5.5 and GPT-6 Astra; Industry-leading inference efficiency: 178 tokens/second throughput at $0.14 / $0.28 per million tokens; High-precision open agent automation with 66.6% on AutomationBench-AA and 1746 GDPval-AA Elo. Full pillar-by-pillar numbers are in the benchmark tables above.

What should you watch out for with DeepSeek-V4.1-Flash-1017?↓

Known trade-offs include: Lower performance on raw interactive CLI tools (42.3 Terminal-Bench 4.0) relative to Kimi K3.1 Pro. Weigh these against the strengths above for your specific workload.