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 North Mini Code for agentic software engineering, code generation, and terminal tasks or efficient sparse moe — 3b active of 30b, runs on a single h100.
Hunyuan Hy3 (Tencent) and North Mini Code (Cohere) 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. North Mini Code is cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. The breakdown below works through their capabilities and ideal use cases so you can match one to your task.
Key differences
Context window: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: Hunyuan Hy3 is the newer model by about 27 days (released July 6, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Hunyuan Hy3
North Mini Code
Provider
Tencent (China)
Cohere (Global)
Released
July 6, 2026
June 9, 2026
Context window
256K (~384 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
67.6%
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.
Agentic software engineering, code generation, and terminal tasks: North Mini Code — A core design strength of North Mini Code.
Efficient sparse MoE — 3B active of 30B, runs on a single H100: North Mini Code — A core design strength of North Mini Code.
High throughput (up to 2.8x Devstral Small 2) at low latency: North Mini Code — A core design strength of North Mini Code.
Which should you pick?
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 agentic software engineering, code generation, and terminal tasks: North Mini 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.
North Mini Code: where it fits
Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. Released June 9, 2026 by Cohere, it is built for agentic software engineering, code generation, and terminal tasks, efficient sparse MoE — 3B active of 30B, runs on a single H100, high throughput (up to 2.8x Devstral Small 2) at low latency, and fully open weights under Apache 2.0 with fp8 and 4-bit builds.
Its trade-offs: text-only and coding-specialized — not multimodal or general-purpose, and 256K context and modest general-intelligence index trail frontier models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Hunyuan Hy3 and North Mini Code overlap enough that the right pick depends on your specific job. 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, North Mini Code for agentic software engineering, code generation, and terminal tasks. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Hunyuan Hy3 or North Mini Code better for coding?
Public SWE-Bench figures are not available for Hunyuan Hy3, 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 North Mini Code leans toward agentic software engineering, code generation, and terminal tasks, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy3 or North Mini Code?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Hunyuan Hy3 and North Mini Code together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy3, North Mini 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 North Mini Code?
Hunyuan Hy3 — released July 6, 2026, about 27 days after North Mini Code.
Hunyuan Hy3 vs North Mini Code
Tencent · China | Cohere · Global · 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 North Mini Code for agentic software engineering, code generation, and terminal tasks or efficient sparse moe — 3b active of 30b, runs on a single h100.
Hunyuan Hy3 (Tencent) and North Mini Code (Cohere) 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. North Mini Code is cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. The breakdown below works through their capabilities and ideal use cases so you can match one to your task.
Key differences at a glance
▸Context window: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: Hunyuan Hy3 is the newer model by about 27 days (released July 6, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Hunyuan Hy3
North Mini Code
Provider
Tencent (China)
Cohere (Global)
Released
July 6, 2026
June 9, 2026
Context window
256K (~384 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
67.6%
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.
Agentic software engineering, code generation, and terminal tasks
North Mini Code
A core design strength of North Mini Code.
Efficient sparse MoE — 3B active of 30B, runs on a single H100
North Mini Code
A core design strength of North Mini Code.
High throughput (up to 2.8x Devstral Small 2) at low latency
North Mini Code
A core design strength of North Mini Code.
Which should you pick?
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 agentic software engineering, code generation, and terminal tasks
→ North Mini 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.
North Mini Code: where it fits
Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. Released June 9, 2026 by Cohere, it is built for agentic software engineering, code generation, and terminal tasks, efficient sparse MoE — 3B active of 30B, runs on a single H100, high throughput (up to 2.8x Devstral Small 2) at low latency, and fully open weights under Apache 2.0 with fp8 and 4-bit builds.
Its trade-offs: text-only and coding-specialized — not multimodal or general-purpose, and 256K context and modest general-intelligence index trail frontier models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Hunyuan Hy3 and North Mini Code overlap enough that the right pick depends on your specific job. 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, North Mini Code for agentic software engineering, code generation, and terminal tasks. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Hunyuan Hy3 and North Mini 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 North Mini Code better for coding?
Public SWE-Bench figures are not available for Hunyuan Hy3, 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 North Mini Code leans toward agentic software engineering, code generation, and terminal tasks, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy3 or North Mini Code?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Hunyuan Hy3 and North Mini Code together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy3, North Mini 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 North Mini Code?
Hunyuan Hy3 — released July 6, 2026, about 27 days after North Mini 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.