Kimi K3 vs DeepSeek-V4-Pro
Kimi K3 wins on Multimodal; DeepSeek-V4-Pro wins on Coding. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.
Verdict at a glance
Choose Kimi K3 if you…
- Best-in-class long text
- Open-source and self-hostable
- Strong codebase understanding
- Fair price
- Best for: Long-document reading, Codebase analysis, Chinese
Choose DeepSeek-V4-Pro if you…
- Strongest open source
- Value champion
- Excellent math reasoning
- Extremely low price
- Best for: Coding, Math reasoning, Open-source deployment
Head-to-head aggregate scores
Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.
Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.
Specs & pricing — every field side by side
List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.
| Dimension | Kimi K3 | DeepSeek-V4-Pro | Verdict |
|---|---|---|---|
| Vendor | Moonshot AI (CN) | DeepSeek (CN) | Different vendors |
| Released | 2026.06 | 2026.04 | Kimi K3 is newer |
| Overall (rank) | 77 · #8 | 77 · #8 | Tie |
| Coding | 71 · #11 | 79 · #5 | DeepSeek-V4-Pro +8 |
| Multimodal | 81 · #10 | 77 · #13 | Kimi K3 +4 |
| Context window | 256K | 1M | DeepSeek-V4-Pro larger |
| Max output | 64K | 128K | Kimi K3 longer |
| Effective-context | 99 | 94 | Kimi K3 more reliable |
| Input $/1M | $3 | $0.44 | DeepSeek-V4-Pro cheaper |
| Output $/1M | $15 | $1.32 | DeepSeek-V4-Pro cheaper |
| Cache discount | custom | none | DeepSeek-V4-Pro deeper |
| Speed | ~45 tok/s | ~70 tok/s | DeepSeek-V4-Pro faster |
| TTFT | 0.7s | 0.5s | DeepSeek-V4-Pro snappier |
| Function calling | 80 | 82 | DeepSeek-V4-Pro ahead |
| Refusal rate | ~6% | ~5% | DeepSeek-V4-Pro less restrictive |
| English | 75 | 82 | DeepSeek-V4-Pro |
| Chinese | 92 | 85 | Kimi K3 |
| Modalities | text, image | text | different coverage |
| Open weights | Yes | Yes | Both open |
| Fine-tuning | No | Yes | |
| Free tier | Kimi App free; free quota on the open platform | DeepSeek App free; new API users receive credits | |
| SOC2 / no-train | no / yes | no / yes | |
| Private deployment | Yes | Yes | Both support it |
Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.
Dimension-by-dimension analysis
Reasoning & overall intelligence
The two are level on the overall aggregate (77/100 each), a gap inside the 3-point band where rankings are statistically indistinguishable and task-specific results can swap.
Agentic coding
This is a modest gap: DeepSeek-V4-Pro scores 79 against 71. On multi-file edits, SWE-style tickets and long-horizon agent loops DeepSeek-V4-Pro needs fewer correction turns; Kimi K3 is still competent for scripts and assisted completion but trails as task complexity rises.
Multimodal
Kimi K3 leads multimodal 81 vs 77. A concrete modality difference: Kimi K3 additionally handles image. Neither emits native video, so the comparison is about parsing images and documents, not generation.
Speed & latency
DeepSeek-V4-Pro is faster in interactive use: ~70 tok/s with 0.5s TTFT versus ~45 tok/s with 0.7s TTFT (about 1.6× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.
Context: window vs usable recall
Nominal windows are 256K for Kimi K3 and 1M for DeepSeek-V4-Pro. Crucially, the larger nominal window does not win on usable recall: DeepSeek-V4-Pro advertises 1M but Kimi K3 scores higher on effective-context (99 vs 94), i.e. it actually retains more of what it was given.
Price & total cost
DeepSeek-V4-Pro is the cheaper API at $0.44/$1.32 versus Kimi K3 at $3/$15 per 1M input/output tokens — list input is about 6.8× lower.
Chinese vs English
English: Kimi K3 75 vs DeepSeek-V4-Pro 82. Chinese: 92 vs 85. For Chinese-language production, Kimi K3 is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.
Tool use & ecosystem
Function-calling score: Kimi K3 80 vs DeepSeek-V4-Pro 82, so DeepSeek-V4-Pro has the edge on structured tool use. Fine-tuning is available from DeepSeek-V4-Pro. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.
Cost worked example — same workload, real token math
Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.
| Scenario · per month | Kimi K3 | DeepSeek-V4-Pro | Gap |
|---|---|---|---|
| List priceno cache applied | $750100M in × $3 + 30M out × $15 | $84100M in × $0.44 + 30M out × $1.32 | 8.93×gap |
| With caching90% of inputs cache-hit | $750no published cache discount | $84no published cache discount | 8.93×gap |
Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.