DeepSeek V4.1 Flash vs Kimi K3
At a Glance
| Compare |  DeepSeek V4.1 FlashDeepSeek |  Kimi K3Moonshot AI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #17 of 4670.3 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | #5 of 44$0.022 per LiveBench case | #30 of 44$0.194 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #21 of 3852.5 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.15DeepSeek ↗ · Sep 10, 2026 | $2.85Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $0.60Deepinfra ↗ · Sep 22, 2026 | $14.25Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1,049K | 1,049K |
| Model facts checked | Sep 10, 2026View model evidence → | Aug 28, 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
| Benchmark | DeepSeek-V4.1-Flash | Kimi-K3 |
|---|---|---|
| LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · statistical tie | 4.8899% of row best · score · Deepseek V4.1 Flash (Max); 95% CI [3.54852933, 6.21109128]; sessions 20080; observations 2295632; rank 12 | 6.22100% of row best · score · Kimi K3 (Max); 95% CI [5.59393783, 6.84323085]; sessions 108615; observations 9086177; rank 8 |
| LiveBench2026-06-25 · overall · leader | 83.20100% of row best · percent · deepseek-v4.1-flash-max · 36,355 output tokens / case | 81.0297% of row best · percent · kimi-k3 · 13,647 output tokens / case |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 88.03100% of row best · points · DeepSeek V4.1 Flash (max) · 18,199 output tokens / case | 88.19100% of row best · points · Kimi K3 · 15,023 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above · 1 tie | 1 benchmark winNo overall winner | 0 benchmark winsNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Quality Versus Estimated Output Cost
Side-by-Side Facts
| Field | DeepSeek-V4.1-Flash | Kimi-K3 |
|---|---|---|
| Developer | DeepSeek | Moonshot AI |
| Family | Deepseek V4 1 | Kimi K3 |
| Model | DeepSeek-V4.1-Flash | Kimi-K3 |
| Version | DeepSeek-V4.1-Flash | Kimi-K3 |
| Lifecycle | active | active |
| Released | 2026-09-10 | 2026-07-16 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,049K | 1,049K |
| Total parameters | 763.2B | 2.8T |
| Active parameters | Unknown | 104B |
| License | mit | other |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | DeepSeek (Standard), Deepinfra (Standard), Together Ai (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | agents, chat, fim, generation, reasoning, responses, structured_outputs, tools, vision | chat, generation, reasoning |
| Architecture design | Causal Encoder-Decoder (20 encoder + 20 decoder layers) | Unknown |
| Backbone parameters | 552000000000 parameters | Unknown |
| Active parameters during decode | 16000000000 parameters | Unknown |
| Active parameters during prefill | 8000000000 parameters | Unknown |
| Pre-training corpus | 45000000000000 tokens | Unknown |
| Reasoning effort range | 1–100 | Unknown |
| Routed experts per MoE layer | 384 experts | Unknown |
| Routed experts per token | 6 experts | Unknown |
| Transformer layers | 40 layers | Unknown |
DeepSeek V4.1 Flash Capabilities
Kimi K3 Capabilities
Related Comparisons
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|---|---|---|---|
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Primary Evidence
Sources and Freshness
Questions
DeepSeek V4.1 Flash vs Kimi K3 FAQs
Is DeepSeek V4.1 Flash or Kimi K3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V4.1 Flash and Kimi K3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, DeepSeek V4.1 Flash or Kimi K3?+
DeepSeek V4.1 Flash is $0.15 and Kimi K3 is $2.85 per million tokens, so DeepSeek V4.1 Flash is cheaper on this metric. DeepSeek V4.1 Flash is $0.60 and Kimi K3 is $14.25 per million tokens, so DeepSeek V4.1 Flash is cheaper on this metric.
Which has a larger context window, DeepSeek V4.1 Flash or Kimi K3?+
Neither model has a larger sourced context window in this comparison. DeepSeek V4.1 Flash is 1,049K and Kimi K3 is 1,049K.
Which performs better in benchmarks, DeepSeek V4.1 Flash or Kimi K3?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can DeepSeek V4.1 Flash or Kimi K3 be self-hosted?+
Both models have the same recorded self-hosting status: supported. DeepSeek V4.1 Flash is open weight; Kimi K3 is open weight.
Can DeepSeek V4.1 Flash and Kimi K3 understand images?+
DeepSeek V4.1 Flash is documented with image input; Kimi K3 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, DeepSeek V4.1 Flash or Kimi K3?+
Neither has a larger sourced maximum output. DeepSeek V4.1 Flash is 393K and Kimi K3 is —.
Do DeepSeek V4.1 Flash and Kimi K3 support reasoning and tool use?+
DeepSeek V4.1 Flash: reasoning, tool calling, and image input. Kimi K3: reasoning and image input. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek V4.1 Flash or Kimi K3?+
DeepSeek V4.1 Flash has 3 sourced provider routes; Kimi K3 has 5, so Kimi K3 has broader tracked availability.
Which offers better value, DeepSeek V4.1 Flash or Kimi K3?+
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.