Pick DeepSeek V4-Flash for exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens or mit-licensed open weights — free to self-host or run via a western host. 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-Flash (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-Flash is deepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens. 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-Flash 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-Flash is the newer model by about 4 months (released July 31, 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-Flash
Gemma 4
Provider
DeepSeek (China)
Google (US)
Released
July 31, 2026
April 2, 2026
Context window
1M (~1,500 pages)
256K (~384 pages)
Price (in/out)
$0.14/$0.28 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
Exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens: DeepSeek V4-Flash — Its 1M window holds about 3.9× more than Gemma 4's 256K in a single prompt.
MIT-licensed open weights — free to self-host or run via a Western host: DeepSeek V4-Flash — DeepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens — and it carries the larger 1M context.
1M-token context window: DeepSeek V4-Flash — DeepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens — and it is the newer of the two.
Self-hosted, data-private deployment: Gemma 4 — DeepSeek V4-Flash is comparatively weak here — deepSeek's own hosted API stores data in China; self-host or use a Western host for privacy
Running locally or on edge devices: Gemma 4 — Gemma 4 lists running locally or on edge devices among its strengths; DeepSeek V4-Flash does not.
Fine-tuning on your own data: Gemma 4 — Gemma 4 lists fine-tuning on your own data among its strengths; DeepSeek V4-Flash 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-Flash's $0.14/$0.28 per 1M tokens.
Largest single-prompt input: DeepSeek V4-Flash — 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-Flash, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: DeepSeek V4-Flash — Larger 1M window fits more in one prompt.
Anyone whose priority is exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens: DeepSeek V4-Flash — 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-Flash — Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
DeepSeek V4-Flash: where it fits
DeepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens. Released July 31, 2026 by DeepSeek, it is built for exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens, mIT-licensed open weights — free to self-host or run via a Western host, 1M-token context window, and strong coding and agentic performance for the price (DeepSeek reports 82.7 on Terminal-Bench 2.1).
Its trade-offs are real: coding/agentic figures like Terminal-Bench 82.7 are DeepSeek's own, not independently reproduced, text and code focused — not a full multimodal model, deepSeek's own hosted API stores data in China; self-host or use a Western host for privacy, and below the top frontier models on overall intelligence. At $0.14 in / $0.28 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-Flash (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-Flash 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-Flash leans toward exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens 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-Flash or Gemma 4?
Gemma 4 is cheaper — $0.14/$0.28 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
DeepSeek V4-Flash — 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-Flash and Gemma 4 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Flash, 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-Flash or Gemma 4?
DeepSeek V4-Flash — released July 31, 2026, about 4 months after Gemma 4.
DeepSeek V4-Flash vs Gemma 4
DeepSeek · China | Google · US · Updated June 2026
Quick verdict
Pick DeepSeek V4-Flash for exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens or mit-licensed open weights — free to self-host or run via a western host. 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-Flash (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-Flash is deepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens. 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-Flash 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-Flash is the newer model by about 4 months (released July 31, 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
DeepSeek V4-Flash
Gemma 4
Provider
DeepSeek (China)
Google (US)
Released
July 31, 2026
April 2, 2026
Context window
1M (~1,500 pages)
256K (~384 pages)
Price (in/out)
$0.14/$0.28 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
Exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens
DeepSeek V4-Flash
Its 1M window holds about 3.9× more than Gemma 4's 256K in a single prompt.
MIT-licensed open weights — free to self-host or run via a Western host
DeepSeek V4-Flash
DeepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens — and it carries the larger 1M context.
1M-token context window
DeepSeek V4-Flash
DeepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens — and it is the newer of the two.
Self-hosted, data-private deployment
Gemma 4
DeepSeek V4-Flash is comparatively weak here — deepSeek's own hosted API stores data in China; self-host or use a Western host for privacy
Running locally or on edge devices
Gemma 4
Gemma 4 lists running locally or on edge devices among its strengths; DeepSeek V4-Flash does not.
Fine-tuning on your own data
Gemma 4
Gemma 4 lists fine-tuning on your own data among its strengths; DeepSeek V4-Flash 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-Flash's $0.14/$0.28 per 1M tokens.
Largest single-prompt input
DeepSeek V4-Flash
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-Flash, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ DeepSeek V4-Flash
Larger 1M window fits more in one prompt.
Anyone whose priority is exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens
→ DeepSeek V4-Flash
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-Flash
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
DeepSeek V4-Flash: where it fits
DeepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens. Released July 31, 2026 by DeepSeek, it is built for exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens, mIT-licensed open weights — free to self-host or run via a Western host, 1M-token context window, and strong coding and agentic performance for the price (DeepSeek reports 82.7 on Terminal-Bench 2.1).
Its trade-offs are real: coding/agentic figures like Terminal-Bench 82.7 are DeepSeek's own, not independently reproduced, text and code focused — not a full multimodal model, deepSeek's own hosted API stores data in China; self-host or use a Western host for privacy, and below the top frontier models on overall intelligence. At $0.14 in / $0.28 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-Flash (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-Flash 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.
Is DeepSeek V4-Flash 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-Flash leans toward exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens 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-Flash or Gemma 4?
Gemma 4 is cheaper — $0.14/$0.28 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
DeepSeek V4-Flash — 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-Flash and Gemma 4 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Flash, 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-Flash or Gemma 4?
DeepSeek V4-Flash — released July 31, 2026, about 4 months 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.