DeepSeek V4.1 Flash 1017 vs Kimi K3

DeepSeek V4.1 Flash 1017 (2026) and Kimi K3 (2026) are frontier-tier reasoning models from DeepSeek and Moonshot AI. Both ship a 1M-token context window. On Google-Proof Q&A, DeepSeek V4.1 Flash 1017 leads by 0.1 pts. On pricing, DeepSeek V4.1 Flash 1017 ranges from $0.15 to $0.30/1M input tokens by tier; Kimi K3 costs $3/1M input tokens. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

DeepSeek V4.1 Flash 1017 is safer overall; choose Kimi K3 when long-context analysis matters.

Decision scorecard

Local evidence first
SignalDeepSeek V4.1 Flash 1017Kimi K3
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentsreasoning-heavy apps, multimodal apps, and tool-calling agents
Decision fitRAG, Agents, and Long contextRAG, Agents, and Long context
Context window1M1M
Cheapest output$0.60/1M tokens$15/1M tokens
Provider routes6 tracked3 tracked
Shared benchmarksGoogle-Proof Q&A leader4 shared

Decision tradeoffs

Choose DeepSeek V4.1 Flash 1017 when...
  • DeepSeek V4.1 Flash 1017 holds a shared-benchmark lead on Google-Proof Q&A, ahead by 0.1 points.
  • DeepSeek V4.1 Flash 1017 has the lower cheapest tracked output price at $0.60/1M tokens.
  • DeepSeek V4.1 Flash 1017 has broader tracked provider coverage for fallback and route flexibility.
  • Local decision data tags DeepSeek V4.1 Flash 1017 for RAG, Agents, and Long context.
Choose Kimi K3 when...
  • Kimi K3 holds a shared-benchmark lead on Humanity's Last Exam, ahead by 0.9 points.
  • Kimi K3 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Kimi K3 for RAG, Agents, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate DeepSeek V4.1 Flash 1017

DeepSeek V4.1 Flash 1017

$270

Cheapest tracked route/tier: DeepSeek Platform Off-peak

Kimi K3

$6,150

Cheapest tracked route/tier: Moonshot AI Kimi

Estimated monthly gap: $5,880. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

DeepSeek V4.1 Flash 1017 -> Kimi K3
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Kimi K3 is $14.40/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Kimi K3 -> DeepSeek V4.1 Flash 1017
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • DeepSeek V4.1 Flash 1017 is $14.40/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.

Specs

Specification
Released2026-10-172026-07-14
Context window1M1M
Parameters552B2.8T (104B active)
ArchitectureMixture of ExpertsMixture of Experts
LicenseMITOSI-approvedKimi K3 License
OpennessOpen sourceOpen weights
WeightsAvailableAvailable
CodeUnknownUnknown
Commercial usePermittedRestricted
Knowledge cutoff--

Pricing and availability

Pricing attributeDeepSeek V4.1 Flash 1017Kimi K3
Input price
Off-peak
$0.15/1M tokens
All hours outside DeepSeek peak windows, including weekends and Chinese public holidays. Cache-read input: $0.003 per 1M tokens; cache-miss input: $0.15 per 1M; output: $0.60 per 1M.
Peak
$0.30/1M tokens
01:00-04:00 and 06:00-10:00 UTC, Monday-Friday, excluding Chinese public holidays. 2x off-peak. Cache-read input: $0.006 per 1M tokens; cache-miss input: $0.30 per 1M; output: $1.20 per 1M.
$3/1M tokens
Output price
Off-peak
$0.60/1M tokens
All hours outside DeepSeek peak windows, including weekends and Chinese public holidays. Cache-read input: $0.003 per 1M tokens; cache-miss input: $0.15 per 1M; output: $0.60 per 1M.
Peak
$1.20/1M tokens
01:00-04:00 and 06:00-10:00 UTC, Monday-Friday, excluding Chinese public holidays. 2x off-peak. Cache-read input: $0.006 per 1M tokens; cache-miss input: $0.30 per 1M; output: $1.20 per 1M.
$15/1M tokens
Providers

Capabilities

CapabilityDeepSeek V4.1 Flash 1017Kimi K3
VisionYesYes
MultimodalYesYes
ReasoningYesYes
JSON / Tool useYesYes
Structured outputsYesYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkDeepSeek V4.1 Flash 1017Kimi K3
Google-Proof Q&A93.293.1
Humanity's Last Exam42.643.5
AutomationBench60.530.8
DeepSWE 1.177.068.5

Deep dive

On shared benchmark coverage, Google-Proof Q&A has DeepSeek V4.1 Flash 1017 at 93.2 and Kimi K3 at 93.1, with DeepSeek V4.1 Flash 1017 ahead by 0.1 points; Humanity's Last Exam has DeepSeek V4.1 Flash 1017 at 42.6 and Kimi K3 at 43.5, with Kimi K3 ahead by 0.9 points; AutomationBench has DeepSeek V4.1 Flash 1017 at 60.5 and Kimi K3 at 30.8, with DeepSeek V4.1 Flash 1017 ahead by 29.7 points. The largest visible gap is 29.7 points on AutomationBench, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint is close: both models cover vision, multimodal input, reasoning mode, JSON / Tool use, and JSON / Tool use. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

For cost, DeepSeek V4.1 Flash 1017 lists tiered pricing: Off-peak is $0.15/1M input and $0.60/1M output; Peak is $0.30/1M input and $1.20/1M output, while Kimi K3 lists $3/1M input and $15/1M output tokens on the cheapest listed provider. A 70/30 input-output blend puts DeepSeek V4.1 Flash 1017 lower by about $6.31 per million blended tokens. For tiered pricing, this cheapest-route view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 6 providers versus 3, so concentration risk also matters.

Choose DeepSeek V4.1 Flash 1017 when vision-heavy evaluation, lower cheapest-tier input-token cost, and broader provider choice are central to the workload. Choose Kimi K3 when long-context analysis and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.

FAQ

Which has a larger context window, DeepSeek V4.1 Flash 1017 or Kimi K3?

Kimi K3 supports 1M tokens, while DeepSeek V4.1 Flash 1017 supports 1M tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, DeepSeek V4.1 Flash 1017 or Kimi K3?

DeepSeek V4.1 Flash 1017 lists tiered pricing: Off-peak is $0.15/1M input and $0.60/1M output; Peak is $0.30/1M input and $1.20/1M output. Kimi K3 lists $3/1M input and $15/1M output tokens on the cheapest listed provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.

Is DeepSeek V4.1 Flash 1017 or Kimi K3 open source?

DeepSeek V4.1 Flash 1017 is listed under MIT. Kimi K3 is listed under Kimi K3 License. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, DeepSeek V4.1 Flash 1017 or Kimi K3?

Both DeepSeek V4.1 Flash 1017 and Kimi K3 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Which is better for multimodal input, DeepSeek V4.1 Flash 1017 or Kimi K3?

Both DeepSeek V4.1 Flash 1017 and Kimi K3 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Where can I run DeepSeek V4.1 Flash 1017 and Kimi K3?

DeepSeek V4.1 Flash 1017 is available on DeepSeek Platform, Vercel AI Gateway, OpenRouter, DeepInfra, and Together AI. Kimi K3 is available on Moonshot AI Kimi, OpenRouter, and Featherless. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-10-17. Data sourced from public model cards and provider documentation.