Pick Gemma 4 26B A4B for fast, cheap inference from a sparse moe (3.8b active of 25.2b total) or near-31b-dense quality at a fraction of the compute and memory-bandwidth cost. Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). On a tight budget at scale, Gemma 4 26B A4B is the value pick.
Gemma 4 26B A4B (Google, US) and Hunyuan Hy4 Preview (Tencent, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Gemma 4 26B A4B is an Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. 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. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Gemma 4 26B A4B is about 7× cheaper on input ($0.12/$0.37 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 5 months (released August 28, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Gemma 4 26B A4B
Hunyuan Hy4 Preview
Provider
Google (US)
Tencent (China)
Released
April 2, 2026
August 28, 2026
Context window
256K (~393 pages)
1M+ tokens (~1,500 pages)
Price (in/out)
$0.12/$0.37 per 1M tokens
$0.834/$2.501 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, video, code
text
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total): Gemma 4 26B A4B — At $0.12/$0.37 per 1M tokens it undercuts Hunyuan Hy4 Preview ($0.834/$2.501 per 1M tokens), and that gap compounds at volume.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost: Gemma 4 26B A4B — An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost — and it runs cheaper at $0.12/$0.37 per 1M tokens.
Strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6): Gemma 4 26B A4B — Gemma 4 26B A4B lists strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6) among its strengths; Hunyuan Hy4 Preview does not.
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 — 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.
SWE-bench Multilingual (82.9): Hunyuan Hy4 Preview — Hunyuan Hy4 Preview lists sWE-bench Multilingual (82.9) among its strengths; Gemma 4 26B A4B does not.
Lowest cost at scale: Gemma 4 26B A4B — At $0.12/$0.37 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 Gemma 4 26B A4B's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Gemma 4 26B A4B — At $0.12/$0.37 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 fast, cheap inference from a sparse moe (3.8b active of 25.2b total): Gemma 4 26B A4B — It is specifically built for that.
Anyone whose priority is gpqa diamond (92.3): Hunyuan Hy4 Preview — That is its strongest area.
An enterprise with regional data-residency rules: Gemma 4 26B A4B or Hunyuan Hy4 Preview — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Gemma 4 26B A4B: where it fits
An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. Released April 2, 2026 by Google, it is built for fast, cheap inference from a sparse MoE (3.8B active of 25.2B total), near-31B-dense quality at a fraction of the compute and memory-bandwidth cost, strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6), and multimodal input (text/image, plus video processed as frames up to 60s) with native function calling.
Its trade-offs are real: all 25.2B parameters must be loaded into memory even though only 3.8B are active per token, and 256K context trails 1M-token frontier rivals, and this variant has no audio input (audio is E2B/E4B/12B only). At $0.12 in / $0.37 out per million tokens, it sits in the budget price band.
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: 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.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Gemma 4 26B A4B (US) and Hunyuan Hy4 Preview (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Gemma 4 26B A4B 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 Gemma 4 26B A4B or Hunyuan Hy4 Preview 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, Gemma 4 26B A4B leans toward fast, cheap inference from a sparse moe (3.8b active of 25.2b total) while Hunyuan Hy4 Preview leans toward gpqa diamond (92.3), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 26B A4B or Hunyuan Hy4 Preview?
Gemma 4 26B A4B is cheaper — $0.12/$0.37 per 1M tokens vs $0.834/$2.501 per 1M tokens, roughly 7× 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 Gemma 4 26B A4B and Hunyuan Hy4 Preview together?
Yes — a multi-model platform like LumiChats gives you Gemma 4 26B A4B, Hunyuan Hy4 Preview 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, Gemma 4 26B A4B or Hunyuan Hy4 Preview?
Hunyuan Hy4 Preview — released August 28, 2026, about 5 months after Gemma 4 26B A4B.
Gemma 4 26B A4B vs Hunyuan Hy4 Preview
Google · US | Tencent · China · Updated June 2026
Quick verdict
Pick Gemma 4 26B A4B for fast, cheap inference from a sparse moe (3.8b active of 25.2b total) or near-31b-dense quality at a fraction of the compute and memory-bandwidth cost. Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). On a tight budget at scale, Gemma 4 26B A4B is the value pick.
Gemma 4 26B A4B (Google, US) and Hunyuan Hy4 Preview (Tencent, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Gemma 4 26B A4B is an Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. 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. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Gemma 4 26B A4B is about 7× cheaper on input ($0.12/$0.37 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 5 months (released August 28, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Gemma 4 26B A4B
Hunyuan Hy4 Preview
Provider
Google (US)
Tencent (China)
Released
April 2, 2026
August 28, 2026
Context window
256K (~393 pages)
1M+ tokens (~1,500 pages)
Price (in/out)
$0.12/$0.37 per 1M tokens
$0.834/$2.501 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, video, code
text
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total)
Gemma 4 26B A4B
At $0.12/$0.37 per 1M tokens it undercuts Hunyuan Hy4 Preview ($0.834/$2.501 per 1M tokens), and that gap compounds at volume.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost
Gemma 4 26B A4B
An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost — and it runs cheaper at $0.12/$0.37 per 1M tokens.
Gemma 4 26B A4B lists strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6) among its strengths; Hunyuan Hy4 Preview does not.
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
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.
SWE-bench Multilingual (82.9)
Hunyuan Hy4 Preview
Hunyuan Hy4 Preview lists sWE-bench Multilingual (82.9) among its strengths; Gemma 4 26B A4B does not.
Lowest cost at scale
Gemma 4 26B A4B
At $0.12/$0.37 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 Gemma 4 26B A4B's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemma 4 26B A4B
At $0.12/$0.37 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 fast, cheap inference from a sparse moe (3.8b active of 25.2b total)
→ Gemma 4 26B A4B
It is specifically built for that.
Anyone whose priority is gpqa diamond (92.3)
→ Hunyuan Hy4 Preview
That is its strongest area.
An enterprise with regional data-residency rules
→ Gemma 4 26B A4B or Hunyuan Hy4 Preview
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Gemma 4 26B A4B: where it fits
An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. Released April 2, 2026 by Google, it is built for fast, cheap inference from a sparse MoE (3.8B active of 25.2B total), near-31B-dense quality at a fraction of the compute and memory-bandwidth cost, strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6), and multimodal input (text/image, plus video processed as frames up to 60s) with native function calling.
Its trade-offs are real: all 25.2B parameters must be loaded into memory even though only 3.8B are active per token, and 256K context trails 1M-token frontier rivals, and this variant has no audio input (audio is E2B/E4B/12B only). At $0.12 in / $0.37 out per million tokens, it sits in the budget price band.
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: 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.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Gemma 4 26B A4B (US) and Hunyuan Hy4 Preview (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Gemma 4 26B A4B 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 Gemma 4 26B A4B and Hunyuan Hy4 Preview 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 Gemma 4 26B A4B or Hunyuan Hy4 Preview 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, Gemma 4 26B A4B leans toward fast, cheap inference from a sparse moe (3.8b active of 25.2b total) while Hunyuan Hy4 Preview leans toward gpqa diamond (92.3), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 26B A4B or Hunyuan Hy4 Preview?
Gemma 4 26B A4B is cheaper — $0.12/$0.37 per 1M tokens vs $0.834/$2.501 per 1M tokens, roughly 7× 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 Gemma 4 26B A4B and Hunyuan Hy4 Preview together?
Yes — a multi-model platform like LumiChats gives you Gemma 4 26B A4B, Hunyuan Hy4 Preview 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, Gemma 4 26B A4B or Hunyuan Hy4 Preview?
Hunyuan Hy4 Preview — released August 28, 2026, about 5 months after Gemma 4 26B A4B.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.