Pick DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable or 1m-token context with up to 384k output tokens. Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. On a tight budget at scale, Gemma 4 is the value pick.
DeepSeek V4-Pro (DeepSeek, China) and Gemma 4 (Google, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. DeepSeek V4-Pro is deepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: DeepSeek V4-Pro holds 3.9× more — 1M (~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: DeepSeek V4-Pro is the newer model by about 22 days (released April 24, 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
DeepSeek V4-Pro
Gemma 4
Provider
DeepSeek (China)
Google (US)
Released
April 24, 2026
April 2, 2026
Context window
1M (~1,500 pages)
256K (~384 pages)
Price (in/out)
$0.435/$0.87 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable: DeepSeek V4-Pro — DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it carries the larger 1M context.
1M-token context with up to 384K output tokens: DeepSeek V4-Pro — Its 1M window holds about 3.9× more than Gemma 4's 256K in a single prompt.
Permanent low pricing at $0.435/$0.87 per million, set May 2026: DeepSeek V4-Pro — DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it is the newer of the two.
Self-hosted, data-private deployment: Gemma 4 — Gemma 4 lists self-hosted, data-private deployment among its strengths; DeepSeek V4-Pro does not.
Running locally or on edge devices: Gemma 4 — Gemma 4 lists running locally or on edge devices among its strengths; DeepSeek V4-Pro does not.
Fine-tuning on your own data: Gemma 4 — Gemma 4 lists fine-tuning on your own data among its strengths; DeepSeek V4-Pro does not.
Lowest cost at scale: Gemma 4 — Its weights are open, so at volume you pay for your own hardware instead of DeepSeek V4-Pro's $0.435/$0.87 per 1M tokens.
Largest single-prompt input: DeepSeek V4-Pro — Its 1M window is about 3.9× larger than Gemma 4's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Gemma 4 — At Open weight (self-host / free) it undercuts DeepSeek V4-Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: DeepSeek V4-Pro — Larger 1M window fits more in one prompt.
Anyone whose priority is open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable: DeepSeek V4-Pro — It is specifically built for that.
Anyone whose priority is self-hosted, data-private deployment: Gemma 4 — That is its strongest area.
An enterprise with regional data-residency rules: Gemma 4 or DeepSeek V4-Pro — Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
DeepSeek V4-Pro: where it fits
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Released April 24, 2026 by DeepSeek, it is built for open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable, 1M-token context with up to 384K output tokens, permanent low pricing at $0.435/$0.87 per million, set May 2026, and sources place it near the top of open-weight coding, around 80 on SWE-Bench Verified.
Its trade-offs are real: independent SWE-Bench Verified placement is inconsistent across sources, pro and Pro-Max variants are quoted with different scores, text and code only — no image, audio or video, and overlaps DeepSeek V4 and V3.2 already in this comparison. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
Gemma 4: where it fits
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Released April 2, 2026 by Google, it is built for self-hosted, data-private deployment, running locally or on edge devices, fine-tuning on your own data, and multimodal tasks over a 256K context.
Its trade-offs: trails frontier closed models on the hardest tasks, and needs your own hardware to run. 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." DeepSeek V4-Pro (China) and Gemma 4 (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Gemma 4 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 DeepSeek V4-Pro or Gemma 4 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, DeepSeek V4-Pro leans toward open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable while Gemma 4 leans toward self-hosted, data-private deployment, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4-Pro or Gemma 4?
Gemma 4 is cheaper — $0.435/$0.87 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
DeepSeek V4-Pro — 1M 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 DeepSeek V4-Pro and Gemma 4 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Pro, Gemma 4 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, DeepSeek V4-Pro or Gemma 4?
DeepSeek V4-Pro — released April 24, 2026, about 22 days after Gemma 4.
DeepSeek V4-Pro vs Gemma 4
DeepSeek · China | Google · US · Updated June 2026
Quick verdict
Pick DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable or 1m-token context with up to 384k output tokens. Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. On a tight budget at scale, Gemma 4 is the value pick.
DeepSeek V4-Pro (DeepSeek, China) and Gemma 4 (Google, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. DeepSeek V4-Pro is deepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: DeepSeek V4-Pro holds 3.9× more — 1M (~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: DeepSeek V4-Pro is the newer model by about 22 days (released April 24, 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.
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it carries the larger 1M context.
1M-token context with up to 384K output tokens
DeepSeek V4-Pro
Its 1M window holds about 3.9× more than Gemma 4's 256K in a single prompt.
Permanent low pricing at $0.435/$0.87 per million, set May 2026
DeepSeek V4-Pro
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it is the newer of the two.
Self-hosted, data-private deployment
Gemma 4
Gemma 4 lists self-hosted, data-private deployment among its strengths; DeepSeek V4-Pro does not.
Running locally or on edge devices
Gemma 4
Gemma 4 lists running locally or on edge devices among its strengths; DeepSeek V4-Pro does not.
Fine-tuning on your own data
Gemma 4
Gemma 4 lists fine-tuning on your own data among its strengths; DeepSeek V4-Pro does not.
Lowest cost at scale
Gemma 4
Its weights are open, so at volume you pay for your own hardware instead of DeepSeek V4-Pro's $0.435/$0.87 per 1M tokens.
Largest single-prompt input
DeepSeek V4-Pro
Its 1M window is about 3.9× larger than Gemma 4's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemma 4
At Open weight (self-host / free) it undercuts DeepSeek V4-Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
Anyone whose priority is self-hosted, data-private deployment
→ Gemma 4
That is its strongest area.
An enterprise with regional data-residency rules
→ Gemma 4 or DeepSeek V4-Pro
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
DeepSeek V4-Pro: where it fits
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Released April 24, 2026 by DeepSeek, it is built for open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable, 1M-token context with up to 384K output tokens, permanent low pricing at $0.435/$0.87 per million, set May 2026, and sources place it near the top of open-weight coding, around 80 on SWE-Bench Verified.
Its trade-offs are real: independent SWE-Bench Verified placement is inconsistent across sources, pro and Pro-Max variants are quoted with different scores, text and code only — no image, audio or video, and overlaps DeepSeek V4 and V3.2 already in this comparison. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
Gemma 4: where it fits
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Released April 2, 2026 by Google, it is built for self-hosted, data-private deployment, running locally or on edge devices, fine-tuning on your own data, and multimodal tasks over a 256K context.
Its trade-offs: trails frontier closed models on the hardest tasks, and needs your own hardware to run. 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." DeepSeek V4-Pro (China) and Gemma 4 (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Gemma 4 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 DeepSeek V4-Pro and Gemma 4 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.
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, DeepSeek V4-Pro leans toward open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable while Gemma 4 leans toward self-hosted, data-private deployment, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4-Pro or Gemma 4?
Gemma 4 is cheaper — $0.435/$0.87 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
DeepSeek V4-Pro — 1M 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 DeepSeek V4-Pro and Gemma 4 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Pro, Gemma 4 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, DeepSeek V4-Pro or Gemma 4?
DeepSeek V4-Pro — released April 24, 2026, about 22 days after Gemma 4.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.