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 K2.7 Code for long-horizon agentic software engineering or token-efficient reasoning (~30% fewer than k2.6). On a tight budget at scale, Hunyuan Hy3 is the value pick.
Hunyuan Hy3 (Tencent) and Kimi K2.7 Code (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 K2.7 Code is moonshot AI's open-weight 1T-parameter MoE model (32B active) tuned for long-horizon agentic coding, always reasoning yet ~30% more token-efficient than K2.6. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: Kimi K2.7 Code holds 1× more — 256K (~393 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Hunyuan Hy3 is the newer model by about 24 days (released July 6, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Hunyuan Hy3
Kimi K2.7 Code
Provider
Tencent (China)
Moonshot AI (China)
Released
July 6, 2026
June 12, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.95/$4 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, video, 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 core design strength of Hunyuan Hy3.
Runs a 295B model at the cost of a 21B — only 21B parameters active per token: Hunyuan Hy3 — A core design strength of Hunyuan Hy3.
Clean, unrestricted Apache-2.0 license with no geographic carve-out: Hunyuan Hy3 — A core design strength of Hunyuan Hy3.
Long-horizon agentic software engineering: Kimi K2.7 Code — A core design strength of Kimi K2.7 Code.
Token-efficient reasoning (~30% fewer than K2.6): Kimi K2.7 Code — A core design strength of Kimi K2.7 Code.
Open-weight 1T MoE, self-hostable: Kimi K2.7 Code — A core design strength of Kimi K2.7 Code.
Lowest cost at scale: Hunyuan Hy3 — At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Kimi K2.7 Code — Its 256K window is about 1× larger, fitting roughly 393 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Hunyuan Hy3 — At Open weight (self-host / free) it undercuts Kimi K2.7 Code, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Kimi K2.7 Code — 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 long-horizon agentic software engineering: Kimi K2.7 Code — 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 K2.7 Code: where it fits
Moonshot AI's open-weight 1T-parameter MoE model (32B active) tuned for long-horizon agentic coding, always reasoning yet ~30% more token-efficient than K2.6. Released June 12, 2026 by Moonshot AI, it is built for long-horizon agentic software engineering, token-efficient reasoning (~30% fewer than K2.6), open-weight 1T MoE, self-hostable, and multi-turn tool use with preserved reasoning.
Its trade-offs: only self-reported benchmarks; no SWE-Bench Verified, and thinking mode and sampling params can't be disabled. At $0.95 in / $4 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Hunyuan Hy3 and Kimi K2.7 Code overlap enough that the right pick depends on your specific job. Hunyuan Hy3 costs less per token; Kimi K2.7 Code 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 K2.7 Code for long-horizon agentic software engineering. 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 K2.7 Code 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 K2.7 Code leans toward long-horizon agentic software engineering, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy3 or Kimi K2.7 Code?
Hunyuan Hy3 is cheaper — Open weight (self-host / free) vs $0.95/$4 per 1M tokens.
Which has the bigger context window?
Kimi K2.7 Code — 256K vs 256K, about 1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Hunyuan Hy3 and Kimi K2.7 Code together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy3, Kimi K2.7 Code 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 K2.7 Code?
Hunyuan Hy3 — released July 6, 2026, about 24 days after Kimi K2.7 Code.
Hunyuan Hy3 vs Kimi K2.7 Code
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 K2.7 Code for long-horizon agentic software engineering or token-efficient reasoning (~30% fewer than k2.6). On a tight budget at scale, Hunyuan Hy3 is the value pick.
Hunyuan Hy3 (Tencent) and Kimi K2.7 Code (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 K2.7 Code is moonshot AI's open-weight 1T-parameter MoE model (32B active) tuned for long-horizon agentic coding, always reasoning yet ~30% more token-efficient than K2.6. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: Kimi K2.7 Code holds 1× more — 256K (~393 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Hunyuan Hy3 is the newer model by about 24 days (released July 6, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Hunyuan Hy3
Kimi K2.7 Code
Provider
Tencent (China)
Moonshot AI (China)
Released
July 6, 2026
June 12, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.95/$4 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, video, 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 core design strength of Hunyuan Hy3.
Runs a 295B model at the cost of a 21B — only 21B parameters active per token
Hunyuan Hy3
A core design strength of Hunyuan Hy3.
Clean, unrestricted Apache-2.0 license with no geographic carve-out
Hunyuan Hy3
A core design strength of Hunyuan Hy3.
Long-horizon agentic software engineering
Kimi K2.7 Code
A core design strength of Kimi K2.7 Code.
Token-efficient reasoning (~30% fewer than K2.6)
Kimi K2.7 Code
A core design strength of Kimi K2.7 Code.
Open-weight 1T MoE, self-hostable
Kimi K2.7 Code
A core design strength of Kimi K2.7 Code.
Lowest cost at scale
Hunyuan Hy3
At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Kimi K2.7 Code
Its 256K window is about 1× larger, fitting roughly 393 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Hunyuan Hy3
At Open weight (self-host / free) it undercuts Kimi K2.7 Code, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Kimi K2.7 Code
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 long-horizon agentic software engineering
→ Kimi K2.7 Code
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 K2.7 Code: where it fits
Moonshot AI's open-weight 1T-parameter MoE model (32B active) tuned for long-horizon agentic coding, always reasoning yet ~30% more token-efficient than K2.6. Released June 12, 2026 by Moonshot AI, it is built for long-horizon agentic software engineering, token-efficient reasoning (~30% fewer than K2.6), open-weight 1T MoE, self-hostable, and multi-turn tool use with preserved reasoning.
Its trade-offs: only self-reported benchmarks; no SWE-Bench Verified, and thinking mode and sampling params can't be disabled. At $0.95 in / $4 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Hunyuan Hy3 and Kimi K2.7 Code overlap enough that the right pick depends on your specific job. Hunyuan Hy3 costs less per token; Kimi K2.7 Code 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 K2.7 Code for long-horizon agentic software engineering. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Hunyuan Hy3 and Kimi K2.7 Code 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.
Is Hunyuan Hy3 or Kimi K2.7 Code 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 K2.7 Code leans toward long-horizon agentic software engineering, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy3 or Kimi K2.7 Code?
Hunyuan Hy3 is cheaper — Open weight (self-host / free) vs $0.95/$4 per 1M tokens.
Which has the bigger context window?
Kimi K2.7 Code — 256K vs 256K, about 1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Hunyuan Hy3 and Kimi K2.7 Code together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy3, Kimi K2.7 Code 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 K2.7 Code?
Hunyuan Hy3 — released July 6, 2026, about 24 days after Kimi K2.7 Code.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.