Hunyuan Hy3 vs Reflection Beam 1.0
Tencent · China | Reflection AI · US · 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 Reflection Beam 1.0 for 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0 or reflection claims 3-4x less inference compute than rival models (vendor claim).
Hunyuan Hy3 (Tencent, China) and Reflection Beam 1.0 (Reflection AI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Reflection Beam 1.0 is reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Context window: Reflection Beam 1.0 holds 3.9× more — 1M tokens (~1,500 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: Reflection Beam 1.0 is the newer model by about 3 months (released October 16, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | Hunyuan Hy3 | Reflection Beam 1.0 |
|---|---|---|
| Provider | Tencent (China) | Reflection AI (US) |
| Released | July 6, 2026 | October 16, 2026 |
| Context window | 256K (~384 pages) | 1M tokens (~1,500 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 | 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
Reflection Beam 1.0 is comparatively weak here — text-only input; some users report reasoning loops on long agent runs
Runs a 295B model at the cost of a 21B — only 21B parameters active per token
Hunyuan Hy3
Reflection Beam 1.0 is comparatively weak here — headline benchmarks come from Reflection's own model card; independent evaluation was limited at launch
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; Reflection Beam 1.0 does not.
501B-parameter sparse MoE (about 23B active per token) with weights on Hugging Face under Apache 2.0
Reflection Beam 1.0
Its 1M tokens window holds about 3.9× more than Hunyuan Hy3's 256K in a single prompt.
Reflection claims 3-4x less inference compute than rival models (vendor claim)
Reflection Beam 1.0
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models — and it carries the larger 1M tokens context.
Fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task
Reflection Beam 1.0
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models — and it is the newer of the two.
Largest single-prompt input
Reflection Beam 1.0
Its 1M tokens window is about 3.9× larger than Hunyuan Hy3's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ Reflection Beam 1.0
Larger 1M tokens 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 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0
→ Reflection Beam 1.0
That is its strongest area.
An enterprise with regional data-residency rules
→ Reflection Beam 1.0 or Hunyuan Hy3
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
Reflection Beam 1.0: where it fits
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models. Released October 16, 2026 by Reflection AI, it is built for 501B-parameter sparse MoE (about 23B active per token) with weights on Hugging Face under Apache 2.0, reflection claims 3-4x less inference compute than rival models (vendor claim), fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task, and third-party hosts list it from $0.25/$1.00 per million tokens (Nebius, as of Oct 27); Reflection's own API is in free beta.
Its trade-offs: artificial Analysis Intelligence Index of 30, well below DeepSeek V4.1 Flash and GLM-5.3 (45), text-only input; some users report reasoning loops on long agent runs, self-hosting needs about 353 GB of GPU memory even at NVFP4, and kernels are CUDA-only for now, and headline benchmarks come from Reflection's own model card; independent evaluation was limited at launch. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Hunyuan Hy3 (China) and Reflection Beam 1.0 (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Hunyuan Hy3 and Reflection Beam 1.0 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 Hy3 or Reflection Beam 1.0 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 Reflection Beam 1.0 leans toward 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy3 or Reflection Beam 1.0?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Reflection Beam 1.0 — 1M tokens vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Hunyuan Hy3 and Reflection Beam 1.0 together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy3, Reflection Beam 1.0 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 Reflection Beam 1.0?
Reflection Beam 1.0 — released October 16, 2026, about 3 months after Hunyuan Hy3.
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.