Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Pick Mistral NeMo for multilingual understanding across 11+ languages or runs on a single gpu with fp8 quantization-aware training. On a tight budget at scale, Mistral NeMo is the value pick.
Hunyuan Hy4 Preview (Tencent, China) and Mistral NeMo (Mistral, France) 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. Mistral NeMo is a 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Mistral NeMo is about 42× cheaper on input ($0.02/$0.03 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 7.6× more — 1M+ tokens (~1,500 pages) vs 128K (~197 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 26 months (released August 28, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Hunyuan Hy4 Preview
Mistral NeMo
Provider
Tencent (China)
Mistral (France)
Released
August 28, 2026
July 18, 2024
Context window
1M+ tokens (~1,500 pages)
128K (~197 pages)
Price (in/out)
$0.834/$2.501 per 1M tokens
$0.02/$0.03 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text
text
SWE-Bench Verified
Not published
Not published
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 — 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; Mistral NeMo does not.
Multilingual understanding across 11+ languages: Mistral NeMo — A 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU — and it runs cheaper at $0.02/$0.03 per 1M tokens.
Runs on a single GPU with FP8 quantization-aware training: Mistral NeMo — Mistral NeMo lists runs on a single GPU with FP8 quantization-aware training among its strengths; Hunyuan Hy4 Preview does not.
128K-token context for long documents: Mistral NeMo — Mistral NeMo lists 128K-token context for long documents among its strengths; Hunyuan Hy4 Preview does not.
Lowest cost at scale: Mistral NeMo — At $0.02/$0.03 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 7.6× larger than Mistral NeMo's 128K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Mistral NeMo — At $0.02/$0.03 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 multilingual understanding across 11+ languages: Mistral NeMo — That is its strongest area.
An enterprise with regional data-residency rules: Mistral NeMo or Hunyuan Hy4 Preview — Origin (China vs France) 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.
Mistral NeMo: where it fits
A 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU. Released July 18, 2024 by Mistral, it is built for multilingual understanding across 11+ languages, runs on a single GPU with FP8 quantization-aware training, 128K-token context for long documents, and function calling and structured tool use.
Its trade-offs: discontinued - deprecated May 22, 2026 and fully retired July 31, 2026; replaced by Ministral 3 8B, 12B scale trails larger frontier models on complex reasoning and coding, and text-only; no vision or audio input. At $0.02 in / $0.03 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 Mistral NeMo (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Mistral NeMo 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 Mistral NeMo 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 Mistral NeMo leans toward multilingual understanding across 11+ languages, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy4 Preview or Mistral NeMo?
Mistral NeMo is cheaper — $0.834/$2.501 per 1M tokens vs $0.02/$0.03 per 1M tokens, roughly 42× apart on input.
Which has the bigger context window?
Hunyuan Hy4 Preview — 1M+ tokens vs 128K, about 7.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Hunyuan Hy4 Preview and Mistral NeMo together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4 Preview, Mistral NeMo 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 Mistral NeMo?
Hunyuan Hy4 Preview — released August 28, 2026, about 26 months after Mistral NeMo.
Hunyuan Hy4 Preview vs Mistral NeMo
Tencent · China | Mistral · France · Updated June 2026
Quick verdict
Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Pick Mistral NeMo for multilingual understanding across 11+ languages or runs on a single gpu with fp8 quantization-aware training. On a tight budget at scale, Mistral NeMo is the value pick.
Hunyuan Hy4 Preview (Tencent, China) and Mistral NeMo (Mistral, France) 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. Mistral NeMo is a 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Mistral NeMo is about 42× cheaper on input ($0.02/$0.03 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 7.6× more — 1M+ tokens (~1,500 pages) vs 128K (~197 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 26 months (released August 28, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Hunyuan Hy4 Preview
Mistral NeMo
Provider
Tencent (China)
Mistral (France)
Released
August 28, 2026
July 18, 2024
Context window
1M+ tokens (~1,500 pages)
128K (~197 pages)
Price (in/out)
$0.834/$2.501 per 1M tokens
$0.02/$0.03 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text
text
SWE-Bench Verified
Not published
Not published
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
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; Mistral NeMo does not.
Multilingual understanding across 11+ languages
Mistral NeMo
A 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU — and it runs cheaper at $0.02/$0.03 per 1M tokens.
Runs on a single GPU with FP8 quantization-aware training
Mistral NeMo
Mistral NeMo lists runs on a single GPU with FP8 quantization-aware training among its strengths; Hunyuan Hy4 Preview does not.
128K-token context for long documents
Mistral NeMo
Mistral NeMo lists 128K-token context for long documents among its strengths; Hunyuan Hy4 Preview does not.
Lowest cost at scale
Mistral NeMo
At $0.02/$0.03 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 7.6× larger than Mistral NeMo's 128K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Mistral NeMo
At $0.02/$0.03 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 multilingual understanding across 11+ languages
→ Mistral NeMo
That is its strongest area.
An enterprise with regional data-residency rules
→ Mistral NeMo or Hunyuan Hy4 Preview
Origin (China vs France) 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.
Mistral NeMo: where it fits
A 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU. Released July 18, 2024 by Mistral, it is built for multilingual understanding across 11+ languages, runs on a single GPU with FP8 quantization-aware training, 128K-token context for long documents, and function calling and structured tool use.
Its trade-offs: discontinued - deprecated May 22, 2026 and fully retired July 31, 2026; replaced by Ministral 3 8B, 12B scale trails larger frontier models on complex reasoning and coding, and text-only; no vision or audio input. At $0.02 in / $0.03 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 Mistral NeMo (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Mistral NeMo 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 Mistral NeMo 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 Mistral NeMo 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 Mistral NeMo leans toward multilingual understanding across 11+ languages, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy4 Preview or Mistral NeMo?
Mistral NeMo is cheaper — $0.834/$2.501 per 1M tokens vs $0.02/$0.03 per 1M tokens, roughly 42× apart on input.
Which has the bigger context window?
Hunyuan Hy4 Preview — 1M+ tokens vs 128K, about 7.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Hunyuan Hy4 Preview and Mistral NeMo together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4 Preview, Mistral NeMo 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 Mistral NeMo?
Hunyuan Hy4 Preview — released August 28, 2026, about 26 months after Mistral NeMo.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.