Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Pick Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters or open weights under openmdw-1.1, shipped day one in bf16, fp8, nvfp4 and int4 across every major runtime. On a tight budget at scale, Laguna XS 2.1 is the value pick.
Hunyuan Hy4 Preview (Tencent, China) and Laguna XS 2.1 (Poolside, 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 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. Laguna XS 2.1 is a 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Laguna XS 2.1 is about 8.3× cheaper on input ($0.1/$0.2 per 1M tokens vs $0.834/$2.501 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Hunyuan Hy4 Preview holds 3.8× more — 1M+ tokens (~1,500 pages) vs 256K (~393 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 Hy4 Preview is the newer model by about 57 days (released August 28, 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.
Specifications
Spec
Hunyuan Hy4 Preview
Laguna XS 2.1
Provider
Tencent (China)
Poolside (US)
Released
August 28, 2026
July 2, 2026
Context window
1M+ tokens (~1,500 pages)
256K (~393 pages)
Price (in/out)
$0.834/$2.501 per 1M tokens
$0.1/$0.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text
text, code
SWE-Bench Verified
Not published
70.9%
MRCR v2 @ 1M
Not published
Not published
Who wins what
GPQA Diamond (92.3): Hunyuan Hy4 Preview — 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 — and it carries the larger 1M+ tokens context.
Terminal-Bench (85.4): Hunyuan Hy4 Preview — Laguna XS 2.1 is comparatively weak here — weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise
SWE-bench Multilingual (82.9): Hunyuan Hy4 Preview — 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 — and it is the newer of the two.
Remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters: Laguna XS 2.1 — A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven — and it runs cheaper at $0.1/$0.2 per 1M tokens.
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime: Laguna XS 2.1 — Laguna XS 2.1 lists open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime among its strengths; Hunyuan Hy4 Preview does not.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price: Laguna XS 2.1 — At $0.1/$0.2 per 1M tokens it undercuts Hunyuan Hy4 Preview ($0.834/$2.501 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale: Laguna XS 2.1 — At $0.1/$0.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Hunyuan Hy4 Preview — Its 1M+ tokens window is about 3.8× larger than Laguna XS 2.1's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Laguna XS 2.1 — At $0.1/$0.2 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: Hunyuan Hy4 Preview — 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 remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters: Laguna XS 2.1 — That is its strongest area.
An enterprise with regional data-residency rules: Laguna XS 2.1 or Hunyuan Hy4 Preview — Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
Laguna XS 2.1: where it fits
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. Released July 2, 2026 by Poolside, it is built for remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters, open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime, cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price, and unusually transparent evaluation — it publishes its harness, step limits, and sandbox specs.
Its trade-offs: weeks old with no independent replication; every published score traces back to Poolside's own harness, the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case, and weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise. At $0.1 in / $0.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Hunyuan Hy4 Preview (China) and Laguna XS 2.1 (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Laguna XS 2.1 is the cheaper option, which matters at volume. 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.
Frequently asked questions
Is Hunyuan Hy4 Preview or Laguna XS 2.1 better for coding?
Public SWE-Bench figures are not available for Hunyuan Hy4 Preview, 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 Laguna XS 2.1 leans toward remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy4 Preview or Laguna XS 2.1?
Laguna XS 2.1 is cheaper — $0.834/$2.501 per 1M tokens vs $0.1/$0.2 per 1M tokens, roughly 8.3× apart on input.
Which has the bigger context window?
Hunyuan Hy4 Preview — 1M+ tokens vs 256K, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Hunyuan Hy4 Preview and Laguna XS 2.1 together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4 Preview, Laguna XS 2.1 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 Laguna XS 2.1?
Hunyuan Hy4 Preview — released August 28, 2026, about 57 days after Laguna XS 2.1.
Hunyuan Hy4 Preview vs Laguna XS 2.1
Tencent · China | Poolside · US · Updated June 2026
Quick verdict
Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Pick Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters or open weights under openmdw-1.1, shipped day one in bf16, fp8, nvfp4 and int4 across every major runtime. On a tight budget at scale, Laguna XS 2.1 is the value pick.
Hunyuan Hy4 Preview (Tencent, China) and Laguna XS 2.1 (Poolside, 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 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. Laguna XS 2.1 is a 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Laguna XS 2.1 is about 8.3× cheaper on input ($0.1/$0.2 per 1M tokens vs $0.834/$2.501 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Hunyuan Hy4 Preview holds 3.8× more — 1M+ tokens (~1,500 pages) vs 256K (~393 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 Hy4 Preview is the newer model by about 57 days (released August 28, 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 Hy4 Preview
Laguna XS 2.1
Provider
Tencent (China)
Poolside (US)
Released
August 28, 2026
July 2, 2026
Context window
1M+ tokens (~1,500 pages)
256K (~393 pages)
Price (in/out)
$0.834/$2.501 per 1M tokens
$0.1/$0.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text
text, code
SWE-Bench Verified
Not published
70.9%
MRCR v2 @ 1M
Not published
Not published
Who wins what
GPQA Diamond (92.3)
Hunyuan Hy4 Preview
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 — and it carries the larger 1M+ tokens context.
Terminal-Bench (85.4)
Hunyuan Hy4 Preview
Laguna XS 2.1 is comparatively weak here — weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise
SWE-bench Multilingual (82.9)
Hunyuan Hy4 Preview
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 — and it is the newer of the two.
Remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters
Laguna XS 2.1
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven — and it runs cheaper at $0.1/$0.2 per 1M tokens.
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime
Laguna XS 2.1
Laguna XS 2.1 lists open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime among its strengths; Hunyuan Hy4 Preview does not.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price
Laguna XS 2.1
At $0.1/$0.2 per 1M tokens it undercuts Hunyuan Hy4 Preview ($0.834/$2.501 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale
Laguna XS 2.1
At $0.1/$0.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Hunyuan Hy4 Preview
Its 1M+ tokens window is about 3.8× larger than Laguna XS 2.1's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Laguna XS 2.1
At $0.1/$0.2 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
→ Hunyuan Hy4 Preview
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 remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters
→ Laguna XS 2.1
That is its strongest area.
An enterprise with regional data-residency rules
→ Laguna XS 2.1 or Hunyuan Hy4 Preview
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
Laguna XS 2.1: where it fits
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. Released July 2, 2026 by Poolside, it is built for remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters, open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime, cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price, and unusually transparent evaluation — it publishes its harness, step limits, and sandbox specs.
Its trade-offs: weeks old with no independent replication; every published score traces back to Poolside's own harness, the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case, and weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise. At $0.1 in / $0.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Hunyuan Hy4 Preview (China) and Laguna XS 2.1 (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Laguna XS 2.1 is the cheaper option, which matters at volume. 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 Hy4 Preview and Laguna XS 2.1 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 Hy4 Preview or Laguna XS 2.1 better for coding?
Public SWE-Bench figures are not available for Hunyuan Hy4 Preview, 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 Laguna XS 2.1 leans toward remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy4 Preview or Laguna XS 2.1?
Laguna XS 2.1 is cheaper — $0.834/$2.501 per 1M tokens vs $0.1/$0.2 per 1M tokens, roughly 8.3× apart on input.
Which has the bigger context window?
Hunyuan Hy4 Preview — 1M+ tokens vs 256K, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Hunyuan Hy4 Preview and Laguna XS 2.1 together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4 Preview, Laguna XS 2.1 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 Laguna XS 2.1?
Hunyuan Hy4 Preview — released August 28, 2026, about 57 days after Laguna XS 2.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.