Pick Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost or runs a 295b model at the cost of a 21b — only 21b parameters active per token. 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, Hunyuan Hy3 is the value pick.
Hunyuan Hy3 (Tencent) and Kimi K2.5 (Moonshot AI) are two of the models people most often weigh against each other in 2026. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. 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open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7.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
Context window: 256K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: Hunyuan Hy3 is the newer model by about 5 months (released July 6, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Hunyuan Hy3
Kimi K2.5
Provider
Tencent (China)
Moonshot AI (China)
Released
July 6, 2026
January 27, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.6/$2.5 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
Frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost: Hunyuan Hy3 — A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost — and it is the newer of the two.
Runs a 295B model at the cost of a 21B — only 21B parameters active per token: Hunyuan Hy3 — Hunyuan Hy3 lists runs a 295B model at the cost of a 21B — only 21B parameters active per token among its strengths; Kimi K2.5 does not.
Clean, unrestricted Apache-2.0 license with no geographic carve-out: Hunyuan Hy3 — Hunyuan Hy3 lists clean, unrestricted Apache-2.0 license with no geographic carve-out among its strengths; Kimi K2.5 does not.
Native multimodal reasoning and visual coding: Kimi K2.5 — Kimi K2.5 lists native multimodal reasoning and visual coding among its strengths; Hunyuan Hy3 does not.
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; Hunyuan Hy3 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; Hunyuan Hy3 does not.
Lowest cost at scale: Hunyuan Hy3 — Its weights are open, so at volume you pay for your own hardware instead of Kimi K2.5's $0.6/$2.5 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Hunyuan Hy3 — At Open weight (self-host / free) it undercuts Kimi K2.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Kimi K2.5 — Larger 256K window fits more in one prompt.
Anyone whose priority is frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost: Hunyuan Hy3 — It is specifically built for that.
Anyone whose priority is native multimodal reasoning and visual coding: Kimi K2.5 — That is its strongest area.
Hunyuan Hy3: where it fits
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Released July 6, 2026 by Tencent, it is built for frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost, runs a 295B model at the cost of a 21B — only 21B parameters active per token, clean, unrestricted Apache-2.0 license with no geographic carve-out, and broad day-one ecosystem support plus an FP8 checkpoint.
Its trade-offs are real: benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion, and the hosted API is China-jurisdiction, and self-hosting a 295B MoE still needs serious hardware. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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 $0.6 in / $2.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Hunyuan Hy3 and Kimi K2.5 overlap enough that the right pick depends on your specific job. Hunyuan Hy3 costs less per token; Kimi K2.5 holds the larger context; and each leads in its own area — Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost, 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.
Frequently asked questions
Is Hunyuan Hy3 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, Hunyuan Hy3 leans toward frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost 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, Hunyuan Hy3 or Kimi K2.5?
Hunyuan Hy3 is cheaper — Open weight (self-host / free) vs $0.6/$2.5 per 1M tokens.
Which has the bigger context window?
Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Hunyuan Hy3 and Kimi K2.5 together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy3, 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, Hunyuan Hy3 or Kimi K2.5?
Hunyuan Hy3 — released July 6, 2026, about 5 months after Kimi K2.5.
Hunyuan Hy3 vs Kimi K2.5
Tencent · China | Moonshot AI · China · Updated June 2026
Quick verdict
Pick Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost or runs a 295b model at the cost of a 21b — only 21b parameters active per token. 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, Hunyuan Hy3 is the value pick.
Hunyuan Hy3 (Tencent) and Kimi K2.5 (Moonshot AI) are two of the models people most often weigh against each other in 2026. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. 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
▸Context window: 256K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: Hunyuan Hy3 is the newer model by about 5 months (released July 6, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Hunyuan Hy3
Kimi K2.5
Provider
Tencent (China)
Moonshot AI (China)
Released
July 6, 2026
January 27, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.6/$2.5 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
Frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost
Hunyuan Hy3
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost — and it is the newer of the two.
Runs a 295B model at the cost of a 21B — only 21B parameters active per token
Hunyuan Hy3
Hunyuan Hy3 lists runs a 295B model at the cost of a 21B — only 21B parameters active per token among its strengths; Kimi K2.5 does not.
Clean, unrestricted Apache-2.0 license with no geographic carve-out
Hunyuan Hy3
Hunyuan Hy3 lists clean, unrestricted Apache-2.0 license with no geographic carve-out among its strengths; Kimi K2.5 does not.
Native multimodal reasoning and visual coding
Kimi K2.5
Kimi K2.5 lists native multimodal reasoning and visual coding among its strengths; Hunyuan Hy3 does not.
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; Hunyuan Hy3 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; Hunyuan Hy3 does not.
Lowest cost at scale
Hunyuan Hy3
Its weights are open, so at volume you pay for your own hardware instead of Kimi K2.5's $0.6/$2.5 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Hunyuan Hy3
At Open weight (self-host / free) it undercuts Kimi K2.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Kimi K2.5
Larger 256K window fits more in one prompt.
Anyone whose priority is frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost
→ Hunyuan Hy3
It is specifically built for that.
Anyone whose priority is native multimodal reasoning and visual coding
→ Kimi K2.5
That is its strongest area.
Hunyuan Hy3: where it fits
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Released July 6, 2026 by Tencent, it is built for frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost, runs a 295B model at the cost of a 21B — only 21B parameters active per token, clean, unrestricted Apache-2.0 license with no geographic carve-out, and broad day-one ecosystem support plus an FP8 checkpoint.
Its trade-offs are real: benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion, and the hosted API is China-jurisdiction, and self-hosting a 295B MoE still needs serious hardware. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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 $0.6 in / $2.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Hunyuan Hy3 and Kimi K2.5 overlap enough that the right pick depends on your specific job. Hunyuan Hy3 costs less per token; Kimi K2.5 holds the larger context; and each leads in its own area — Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost, 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 Hunyuan Hy3 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.
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, Hunyuan Hy3 leans toward frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost 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, Hunyuan Hy3 or Kimi K2.5?
Hunyuan Hy3 is cheaper — Open weight (self-host / free) vs $0.6/$2.5 per 1M tokens.
Which has the bigger context window?
Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Hunyuan Hy3 and Kimi K2.5 together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy3, 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, Hunyuan Hy3 or Kimi K2.5?
Hunyuan Hy3 — released July 6, 2026, about 5 months after Kimi K2.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.