DeepSeek V4-Pro vs Kimi K2.5
DeepSeek · China | Moonshot AI · China · Updated June 2026
Quick verdict
Pick DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable or 1m-token context with up to 384k output tokens. Pick Kimi K2.5 for native multimodal reasoning and visual coding or agentic tool-calling and self-directed multi-step work. On a tight budget at scale, Kimi K2.5 is the value pick.
DeepSeek V4-Pro (DeepSeek) and Kimi K2.5 (Moonshot AI) are two of the models people most often weigh against each other in 2026. DeepSeek V4-Pro is deepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Kimi K2.5 is moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: Kimi K2.5 is about 1.5× cheaper on input ($0.45/$2.25 per 1M tokens vs $0.66/$1.98 per 1M tokens) — modest, but it adds up at steady volume.
- ▸Context window: DeepSeek V4-Pro holds 3.8× more — 1M (~1,500 pages) vs 256K (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: DeepSeek V4-Pro is the newer model by about 3 months (released April 24, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | DeepSeek V4-Pro | Kimi K2.5 |
|---|---|---|
| Provider | DeepSeek (China) | Moonshot AI (China) |
| Released | April 24, 2026 | January 27, 2026 |
| Context window | 1M (~1,500 pages) | 256K (~393 pages) |
| Price (in/out) | $0.66/$1.98 per 1M tokens | $0.45/$2.25 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, code | text, image, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable
DeepSeek V4-Pro
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it carries the larger 1M context.
1M-token context with up to 384K output tokens
DeepSeek V4-Pro
Its 1M window holds about 3.8× more than Kimi K2.5's 256K in a single prompt.
Permanent low pricing at $0.435/$0.87 per million, set May 2026
DeepSeek V4-Pro
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it is the newer of the two.
Native multimodal reasoning and visual coding
Kimi K2.5
Moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7 — and it runs cheaper at $0.45/$2.25 per 1M tokens.
Agentic tool-calling and self-directed multi-step work
Kimi K2.5
Kimi K2.5 lists agentic tool-calling and self-directed multi-step work among its strengths; DeepSeek V4-Pro does not.
Open-weight (Modified-MIT) — self-hostable at 256K context
Kimi K2.5
Kimi K2.5 lists open-weight (Modified-MIT) — self-hostable at 256K context among its strengths; DeepSeek V4-Pro does not.
Lowest cost at scale
Kimi K2.5
At $0.45/$2.25 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
DeepSeek V4-Pro
Its 1M window is about 3.8× larger than Kimi K2.5's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Kimi K2.5
At $0.45/$2.25 per 1M tokens it undercuts DeepSeek V4-Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ DeepSeek V4-Pro
Larger 1M window fits more in one prompt.
Anyone whose priority is open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable
→ DeepSeek V4-Pro
It is specifically built for that.
Anyone whose priority is native multimodal reasoning and visual coding
→ Kimi K2.5
That is its strongest area.
DeepSeek V4-Pro: where it fits
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Released April 24, 2026 by DeepSeek, it is built for open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable, 1M-token context with up to 384K output tokens, permanent low pricing at $0.435/$0.87 per million, set May 2026, and sources place it near the top of open-weight coding, around 80 on SWE-Bench Verified.
Its trade-offs are real: independent SWE-Bench Verified placement is inconsistent across sources, pro and Pro-Max variants are quoted with different scores, text and code only — no image, audio or video, and overlaps DeepSeek V4 and V3.2 already in this comparison. At $0.66 in / $1.98 out per million tokens, it sits in the budget price band.
Kimi K2.5: where it fits
Moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. Released January 27, 2026 by Moonshot AI, it is built for native multimodal reasoning and visual coding, agentic tool-calling and self-directed multi-step work, open-weight (Modified-MIT) — self-hostable at 256K context, and vendor reports around 76.8% on its own SWE-agent coding harness.
Its trade-offs: its coding score uses Moonshot's own harness, not the standard SWE-Bench Verified protocol, superseded within Moonshot's line by Kimi K2.6 and K2.7, openRouter shows a promo price below Moonshot's $0.60/$2.50 list, and image input but no audio or video. At $0.45 in / $2.25 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
DeepSeek V4-Pro and Kimi K2.5 overlap enough that the right pick depends on your specific job. Kimi K2.5 costs less per token; DeepSeek V4-Pro holds the larger context; and each leads in its own area — DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable, Kimi K2.5 for native multimodal reasoning and visual coding. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both DeepSeek V4-Pro and Kimi K2.5 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is DeepSeek V4-Pro or Kimi K2.5 better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, DeepSeek V4-Pro leans toward open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable while Kimi K2.5 leans toward native multimodal reasoning and visual coding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4-Pro or Kimi K2.5?
Kimi K2.5 is cheaper — $0.66/$1.98 per 1M tokens vs $0.45/$2.25 per 1M tokens, roughly 1.5× apart on input.
Which has the bigger context window?
DeepSeek V4-Pro — 1M vs 256K, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both DeepSeek V4-Pro and Kimi K2.5 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Pro, Kimi K2.5 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, DeepSeek V4-Pro or Kimi K2.5?
DeepSeek V4-Pro — released April 24, 2026, about 3 months after Kimi K2.5.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.