Hunyuan Hy4 Preview vs MiMo-V2.6-Pro
Tencent · China | Xiaomi · China · Updated June 2026
Quick verdict
Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Pick MiMo-V2.6-Pro for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters or 1.02 trillion total parameters, 42b active per token (sparse moe), mit-licensed and self-hostable. On a tight budget at scale, MiMo-V2.6-Pro is the value pick.
Hunyuan Hy4 Preview (Tencent) and MiMo-V2.6-Pro (Xiaomi) are two of the models people most often weigh against each other in 2026. Hunyuan Hy4 Preview is tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. MiMo-V2.6-Pro is xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: MiMo-V2.6-Pro is about 1.9× cheaper on input ($0.435/$0.87 per 1M tokens vs $0.834/$2.501 per 1M tokens) — modest, but it adds up at steady volume.
- ▸Context window: 1M+ tokens vs 1M tokens — 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: MiMo-V2.6-Pro is the newer model by about 25 days (released September 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Hunyuan Hy4 Preview | MiMo-V2.6-Pro |
|---|---|---|
| Provider | Tencent (China) | Xiaomi (China) |
| Released | August 28, 2026 | September 22, 2026 |
| Context window | 1M+ tokens (~1,500 pages) | 1M tokens (~1,573 pages) |
| Price (in/out) | $0.834/$2.501 per 1M tokens | $0.435/$0.87 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text | text, image, video, audio |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
GPQA Diamond (92.3)
Hunyuan Hy4 Preview
Hunyuan Hy4 Preview lists gPQA Diamond (92.3) among its strengths; MiMo-V2.6-Pro does not.
Terminal-Bench (85.4)
Hunyuan Hy4 Preview
MiMo-V2.6-Pro is comparatively weak here — first-generation omnimodal release from Xiaomi's MiMo line — benchmark claims are largely Xiaomi's own reporting, not yet widely independently verified
SWE-bench Multilingual (82.9)
Hunyuan Hy4 Preview
Hunyuan Hy4 Preview lists sWE-bench Multilingual (82.9) among its strengths; MiMo-V2.6-Pro does not.
Natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters
MiMo-V2.6-Pro
Xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026 — and it runs cheaper at $0.435/$0.87 per 1M tokens.
1.02 trillion total parameters, 42B active per token (sparse MoE), MIT-licensed and self-hostable
MiMo-V2.6-Pro
Xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026 — and it is the newer of the two.
Reported Artificial Analysis Intelligence Index score of 46
MiMo-V2.6-Pro
Hunyuan Hy4 Preview is comparatively weak here — sWE-Marathon score still low in absolute terms (31.9) despite a large relative jump
Lowest cost at scale
MiMo-V2.6-Pro
At $0.435/$0.87 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiMo-V2.6-Pro
At $0.435/$0.87 per 1M tokens it undercuts Hunyuan Hy4 Preview, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ MiMo-V2.6-Pro
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is gpqa diamond (92.3)
→ Hunyuan Hy4 Preview
It is specifically built for that.
Anyone whose priority is natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters
→ MiMo-V2.6-Pro
That is its strongest area.
Hunyuan Hy4 Preview: where it fits
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. Released August 28, 2026 by Tencent, it is built for gPQA Diamond (92.3), terminal-Bench (85.4), sWE-bench Multilingual (82.9), and large jump in long-horizon coding vs prior Hunyuan model (DeepSWE 28.0 to 64.3).
Its trade-offs are real: text-only, no native vision support, labeled a 'preview', not yet Tencent's finalized GA flagship, and sWE-Marathon score still low in absolute terms (31.9) despite a large relative jump. At $0.834 in / $2.501 out per million tokens, it sits in the budget price band.
MiMo-V2.6-Pro: where it fits
Xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026. Released September 22, 2026 by Xiaomi, it is built for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters, 1.02 trillion total parameters, 42B active per token (sparse MoE), MIT-licensed and self-hostable, reported Artificial Analysis Intelligence Index score of 46, and a separate 'UltraSpeed' variant reportedly delivers up to 20x faster output than Pro at similar quality for high-throughput use cases.
Its trade-offs: first-generation omnimodal release from Xiaomi's MiMo line — benchmark claims are largely Xiaomi's own reporting, not yet widely independently verified, an Artificial Analysis Index score of 46 trails several established frontier models, and no official API pricing from Xiaomi directly — the listed price reflects third-party inference providers (e.g. OpenRouter), which can change independently of Xiaomi's own terms. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Hunyuan Hy4 Preview and MiMo-V2.6-Pro overlap enough that the right pick depends on your specific job. MiMo-V2.6-Pro costs less per token; MiMo-V2.6-Pro holds the larger context; and each leads in its own area — Hunyuan Hy4 Preview for gpqa diamond (92.3), MiMo-V2.6-Pro for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Hunyuan Hy4 Preview and MiMo-V2.6-Pro 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 Hunyuan Hy4 Preview or MiMo-V2.6-Pro 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 Hy4 Preview leans toward gpqa diamond (92.3) while MiMo-V2.6-Pro leans toward natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy4 Preview or MiMo-V2.6-Pro?
MiMo-V2.6-Pro is cheaper — $0.834/$2.501 per 1M tokens vs $0.435/$0.87 per 1M tokens, roughly 1.9× apart on input.
Which has the bigger context window?
Effectively neither — 1M+ tokens vs 1M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Hunyuan Hy4 Preview and MiMo-V2.6-Pro together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4 Preview, MiMo-V2.6-Pro 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 Hy4 Preview or MiMo-V2.6-Pro?
MiMo-V2.6-Pro — released September 22, 2026, about 25 days after Hunyuan Hy4 Preview.
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.