Pick Apple Foundation Models 3 for runs entirely on-device on iphone - no api call, no per-token cost, works offline or the 20b sparse 'core advanced' variant lifted on-device output quality from 23% to 46% user preference in apple's own testing versus the prior generation. Pick DeepSeek R1 for open-weight reasoning model or transparent chain-of-thought. Choose DeepSeek R1 if you need self-hosting or data privacy; Apple Foundation Models 3 if you want a managed API.
Apple Foundation Models 3 (Apple, US) and DeepSeek R1 (DeepSeek, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Apple Foundation Models 3 is apple's on-device model family - genuinely small context and no API access, but private, offline, and free to run on every iPhone. DeepSeek R1 is the open-weight reasoning model that reset price expectations in early 2025. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: DeepSeek R1 ships open weights you can self-host (hardware cost only, no per-token fee), while Apple Foundation Models 3 is API-metered at Not published. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: DeepSeek R1 holds 31× more — 128K (~192 pages) vs 4K (~6 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Apple Foundation Models 3 is the newer model by about 17 months (released June 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
Apple Foundation Models 3
DeepSeek R1
Provider
Apple (US)
DeepSeek (China)
Released
June 2026
January 2025
Context window
4K (~6 pages)
128K (~192 pages)
Price (in/out)
Not published
$0.55/$2.19 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Runs entirely on-device on iPhone - no API call, no per-token cost, works offline: Apple Foundation Models 3 — Apple's on-device model family - genuinely small context and no API access, but private, offline, and free to run on every iPhone — and it is the newer of the two.
The 20B sparse 'Core Advanced' variant lifted on-device output quality from 23% to 46% user preference in Apple's own testing versus the prior generation: Apple Foundation Models 3 — Apple Foundation Models 3 lists the 20B sparse 'Core Advanced' variant lifted on-device output quality from 23% to 46% user preference in Apple's own testing versus the prior generation among its strengths; DeepSeek R1 does not.
Deep integration with iOS apps via the Foundation Models framework, now open to third-party LLM providers too: Apple Foundation Models 3 — Apple Foundation Models 3 lists deep integration with iOS apps via the Foundation Models framework, now open to third-party LLM providers too among its strengths; DeepSeek R1 does not.
Open-weight reasoning model: DeepSeek R1 — Open weights make this possible at all — Apple Foundation Models 3 is API-only, so it cannot leave the vendor's servers.
Transparent chain-of-thought: DeepSeek R1 — The open-weight reasoning model that reset price expectations in early 2025 — and it carries the larger 128K context.
Low cost: DeepSeek R1 — The open-weight reasoning model that reset price expectations in early 2025 — and its weights are open while Apple Foundation Models 3 is API-only.
Lowest cost at scale: Apple Foundation Models 3 — Its weights are open, so at volume you pay for your own hardware instead of DeepSeek R1's $0.55/$2.19 per 1M tokens.
Largest single-prompt input: DeepSeek R1 — Its 128K window is about 31× larger than Apple Foundation Models 3's 4K, fitting roughly 192 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Apple Foundation Models 3 — At Not published it undercuts DeepSeek R1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: DeepSeek R1 — Larger 128K window fits more in one prompt.
A team with data-privacy or self-hosting needs: DeepSeek R1 — Open weights let you run it on your own hardware; Apple Foundation Models 3 is API-only.
Anyone whose priority is runs entirely on-device on iphone - no api call, no per-token cost, works offline: Apple Foundation Models 3 — It is specifically built for that.
Anyone whose priority is open-weight reasoning model: DeepSeek R1 — That is its strongest area.
An enterprise with regional data-residency rules: Apple Foundation Models 3 or DeepSeek R1 — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Apple Foundation Models 3: where it fits
Apple's on-device model family - genuinely small context and no API access, but private, offline, and free to run on every iPhone. Released June 2026 by Apple, it is built for runs entirely on-device on iPhone - no API call, no per-token cost, works offline, the 20B sparse 'Core Advanced' variant lifted on-device output quality from 23% to 46% user preference in Apple's own testing versus the prior generation, deep integration with iOS apps via the Foundation Models framework, now open to third-party LLM providers too, and zero marginal cost and strong privacy - nothing leaves the device.
Its trade-offs are real: a genuinely small context window (about 4,096 tokens, shared between input and output) - far below cloud frontier models, not comparable in raw capability to frontier cloud models - built for efficiency and privacy, not benchmark leadership, and no public API pricing since it isn't sold per-token - only usable within Apple's own platforms.
DeepSeek R1: where it fits
The open-weight reasoning model that reset price expectations in early 2025. Released January 2025 by DeepSeek, it is built for open-weight reasoning model, transparent chain-of-thought, low cost, and strong maths and code.
Its trade-offs: discontinued - no longer offered as a standalone model via DeepSeek's API as of mid-2026; the legacy alias that used to point to it stopped working July 24, 2026, older than V4, smaller 128K context, and text/code focused. At $0.55 in / $2.19 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. DeepSeek R1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Apple Foundation Models 3 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is Apple Foundation Models 3 or DeepSeek R1 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, Apple Foundation Models 3 leans toward runs entirely on-device on iphone - no api call, no per-token cost, works offline while DeepSeek R1 leans toward open-weight reasoning model, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Apple Foundation Models 3 or DeepSeek R1?
DeepSeek R1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Apple Foundation Models 3 is API-metered at Not published. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
DeepSeek R1 — 128K vs 4K, about 31× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Apple Foundation Models 3 and DeepSeek R1 together?
Yes — a multi-model platform like LumiChats gives you Apple Foundation Models 3, DeepSeek R1 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, Apple Foundation Models 3 or DeepSeek R1?
Apple Foundation Models 3 — released June 2026, about 17 months after DeepSeek R1.
Apple Foundation Models 3 vs DeepSeek R1
Apple · US | DeepSeek · China · Updated June 2026
Quick verdict
Pick Apple Foundation Models 3 for runs entirely on-device on iphone - no api call, no per-token cost, works offline or the 20b sparse 'core advanced' variant lifted on-device output quality from 23% to 46% user preference in apple's own testing versus the prior generation. Pick DeepSeek R1 for open-weight reasoning model or transparent chain-of-thought. Choose DeepSeek R1 if you need self-hosting or data privacy; Apple Foundation Models 3 if you want a managed API.
Apple Foundation Models 3 (Apple, US) and DeepSeek R1 (DeepSeek, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Apple Foundation Models 3 is apple's on-device model family - genuinely small context and no API access, but private, offline, and free to run on every iPhone. DeepSeek R1 is the open-weight reasoning model that reset price expectations in early 2025. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: DeepSeek R1 ships open weights you can self-host (hardware cost only, no per-token fee), while Apple Foundation Models 3 is API-metered at Not published. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: DeepSeek R1 holds 31× more — 128K (~192 pages) vs 4K (~6 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Apple Foundation Models 3 is the newer model by about 17 months (released June 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
Apple Foundation Models 3
DeepSeek R1
Provider
Apple (US)
DeepSeek (China)
Released
June 2026
January 2025
Context window
4K (~6 pages)
128K (~192 pages)
Price (in/out)
Not published
$0.55/$2.19 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Runs entirely on-device on iPhone - no API call, no per-token cost, works offline
Apple Foundation Models 3
Apple's on-device model family - genuinely small context and no API access, but private, offline, and free to run on every iPhone — and it is the newer of the two.
The 20B sparse 'Core Advanced' variant lifted on-device output quality from 23% to 46% user preference in Apple's own testing versus the prior generation
Apple Foundation Models 3
Apple Foundation Models 3 lists the 20B sparse 'Core Advanced' variant lifted on-device output quality from 23% to 46% user preference in Apple's own testing versus the prior generation among its strengths; DeepSeek R1 does not.
Deep integration with iOS apps via the Foundation Models framework, now open to third-party LLM providers too
Apple Foundation Models 3
Apple Foundation Models 3 lists deep integration with iOS apps via the Foundation Models framework, now open to third-party LLM providers too among its strengths; DeepSeek R1 does not.
Open-weight reasoning model
DeepSeek R1
Open weights make this possible at all — Apple Foundation Models 3 is API-only, so it cannot leave the vendor's servers.
Transparent chain-of-thought
DeepSeek R1
The open-weight reasoning model that reset price expectations in early 2025 — and it carries the larger 128K context.
Low cost
DeepSeek R1
The open-weight reasoning model that reset price expectations in early 2025 — and its weights are open while Apple Foundation Models 3 is API-only.
Lowest cost at scale
Apple Foundation Models 3
Its weights are open, so at volume you pay for your own hardware instead of DeepSeek R1's $0.55/$2.19 per 1M tokens.
Largest single-prompt input
DeepSeek R1
Its 128K window is about 31× larger than Apple Foundation Models 3's 4K, fitting roughly 192 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Apple Foundation Models 3
At Not published it undercuts DeepSeek R1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ DeepSeek R1
Larger 128K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ DeepSeek R1
Open weights let you run it on your own hardware; Apple Foundation Models 3 is API-only.
Anyone whose priority is runs entirely on-device on iphone - no api call, no per-token cost, works offline
→ Apple Foundation Models 3
It is specifically built for that.
Anyone whose priority is open-weight reasoning model
→ DeepSeek R1
That is its strongest area.
An enterprise with regional data-residency rules
→ Apple Foundation Models 3 or DeepSeek R1
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Apple Foundation Models 3: where it fits
Apple's on-device model family - genuinely small context and no API access, but private, offline, and free to run on every iPhone. Released June 2026 by Apple, it is built for runs entirely on-device on iPhone - no API call, no per-token cost, works offline, the 20B sparse 'Core Advanced' variant lifted on-device output quality from 23% to 46% user preference in Apple's own testing versus the prior generation, deep integration with iOS apps via the Foundation Models framework, now open to third-party LLM providers too, and zero marginal cost and strong privacy - nothing leaves the device.
Its trade-offs are real: a genuinely small context window (about 4,096 tokens, shared between input and output) - far below cloud frontier models, not comparable in raw capability to frontier cloud models - built for efficiency and privacy, not benchmark leadership, and no public API pricing since it isn't sold per-token - only usable within Apple's own platforms.
DeepSeek R1: where it fits
The open-weight reasoning model that reset price expectations in early 2025. Released January 2025 by DeepSeek, it is built for open-weight reasoning model, transparent chain-of-thought, low cost, and strong maths and code.
Its trade-offs: discontinued - no longer offered as a standalone model via DeepSeek's API as of mid-2026; the legacy alias that used to point to it stopped working July 24, 2026, older than V4, smaller 128K context, and text/code focused. At $0.55 in / $2.19 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. DeepSeek R1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Apple Foundation Models 3 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both Apple Foundation Models 3 and DeepSeek R1 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 Apple Foundation Models 3 or DeepSeek R1 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, Apple Foundation Models 3 leans toward runs entirely on-device on iphone - no api call, no per-token cost, works offline while DeepSeek R1 leans toward open-weight reasoning model, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Apple Foundation Models 3 or DeepSeek R1?
DeepSeek R1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Apple Foundation Models 3 is API-metered at Not published. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
DeepSeek R1 — 128K vs 4K, about 31× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Apple Foundation Models 3 and DeepSeek R1 together?
Yes — a multi-model platform like LumiChats gives you Apple Foundation Models 3, DeepSeek R1 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, Apple Foundation Models 3 or DeepSeek R1?
Apple Foundation Models 3 — released June 2026, about 17 months after DeepSeek R1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.