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DeepSeek

DeepSeek-V4.1-Flash-1017

Released Oct 2026. Open weights, available for self-hosting and fine-tuning.

DeepSeek-V4.1-Flash-1017 is built by DeepSeek and has 11 benchmark results tracked in the public leaderboard. It supports multimodal input, with a context window of 1.05M tokens. At the blended 8:1 input-to-output rate, it costs $0.40 per million tokens.

Blended price$0.40per 1M tokens (8:1)
Context1.05Mtokens
Output speedn/atokens / sec
Benchmarks11results tracked

Where DeepSeek-V4.1-Flash-1017 ranks

The chart below ranks every model in the comparison by overall capability, which is the average of a model's scores across the eight workload axes. DeepSeek-V4.1-Flash-1017 is the red bar. This is the single number to check first: it tells you where the model sits in the current pecking order before you dig into the detail.

Bar chart ranking all ten models by overall capability index, with DeepSeek-V4.1-Flash-1017 highlighted in red.
Every model ranked by overall capability index (0 to 100), averaged across eight workload axes. DeepSeek-V4.1-Flash-1017 is the red bar. Data Today, from llm-stats.com public benchmarks.

Workload strengths

Each row below is the average normalized score across every benchmark tagged with that workload category. A higher number means the model performs better on that kind of task relative to the maximum possible score on those benchmarks. Categories where the model has no published results are shown as n/a.

WorkloadIndex (0–1)
Reasoning50%
Coding54%
Agents49%
Math43%
Vision71%
Long Contextn/a
Writingn/a
Knowledgen/a

How DeepSeek-V4.1-Flash-1017 stacks up against every other model

Below is every head-to-head comparison involving DeepSeek-V4.1-Flash-1017. Each card shows the win/loss tally across all workload axes and headline benchmarks. Tap any matchup for the full breakdown with per-benchmark scores, pricing, and workload recommendations.

Head to head

DeepSeek-V4.1-Flash-1017vs Grok Voice 3.0

DeepSeek-V4.1-Flash-1017 leads 4–1

Head to head

DeepSeek-V4.1-Flash-1017vs Fish Audio Drama 3

DeepSeek-V4.1-Flash-1017 leads 4–2

Head to head

DeepSeek-V4.1-Flash-1017vs Particle-1

Particle-1 leads 5–2

Head to head

DeepSeek-V4.1-Flash-1017vs Gemini 4 Carbon

Gemini 4 Carbon leads 7–0

Head to head

DeepSeek-V4.1-Flash-1017vs Kimi K3.1 Pro

Kimi K3.1 Pro leads 10–0

Head to head

DeepSeek-V4.1-Flash-1017vs Mercury 3

Even at 4–4

Head to head

DeepSeek-V4.1-Flash-1017vs GPT-6.1 Terra

GPT-6.1 Terra leads 4–2

Head to head

DeepSeek-V4.1-Flash-1017vs Muse Spark Open

Muse Spark Open leads 7–1

Head to head

DeepSeek-V4.1-Flash-1017vs Nemotron 3.5 Super VL (120B A12B)

Nemotron 3.5 Super VL (120B A12B) leads 8–2

Head to head

DeepSeek-V4.1-Flash-1017vs Grok Voice 3.0

DeepSeek-V4.1-Flash-1017 leads 4–1

Head to head

DeepSeek-V4.1-Flash-1017vs Fish Audio Drama 3

DeepSeek-V4.1-Flash-1017 leads 4–2

Head to head

DeepSeek-V4.1-Flash-1017vs Particle-1

Particle-1 leads 5–2

Head to head

DeepSeek-V4.1-Flash-1017vs Gemini 4 Carbon

Gemini 4 Carbon leads 7–0

Head to head

DeepSeek-V4.1-Flash-1017vs Kimi K3.1 Pro

Kimi K3.1 Pro leads 10–0

Head to head

DeepSeek-V4.1-Flash-1017vs Mercury 3

Even at 4–4

Head to head

DeepSeek-V4.1-Flash-1017vs GPT-6.1 Terra

GPT-6.1 Terra leads 4–2

Head to head

DeepSeek-V4.1-Flash-1017vs Muse Spark Open

Muse Spark Open leads 7–1

Head to head

DeepSeek-V4.1-Flash-1017vs Nemotron 3.5 Super VL (120B A12B)

Nemotron 3.5 Super VL (120B A12B) leads 8–2


Choose a matchup above, or start from the hub to pick any two models.