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 Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported) or subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck. On a tight budget at scale, Apple Foundation Models 3 is the value pick.
Apple Foundation Models 3 (Apple) and Muse Spark 1.1 (Meta) are two of the models people most often weigh against each other in 2026. 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. Muse Spark 1.1 is meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: Muse Spark 1.1 holds 256× more — 1M (~1,573 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: Muse Spark 1.1 is the newer model by about 38 days (released July 9, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Apple Foundation Models 3
Muse Spark 1.1
Provider
Apple (US)
Meta (US)
Released
June 2026
July 9, 2026
Context window
4K (~6 pages)
1M (~1,573 pages)
Price (in/out)
Not published
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
54.1%
Who wins what
Runs entirely on-device on iPhone - no API call, no per-token cost, works offline: Apple Foundation Models 3 — Apple Foundation Models 3 lists runs entirely on-device on iPhone - no API call, no per-token cost, works offline among its strengths; Muse Spark 1.1 does not.
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; Muse Spark 1.1 does not.
Deep integration with iOS apps via the Foundation Models framework, now open to third-party LLM providers too: Apple Foundation Models 3 — Muse Spark 1.1 is comparatively weak here — uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication
Scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported): Muse Spark 1.1 — Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding — and it carries the larger 1M context.
Subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck: Muse Spark 1.1 — Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding — and it is the newer of the two.
Professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported): Muse Spark 1.1 — Muse Spark 1.1 lists professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported) among its strengths; Apple Foundation Models 3 does not.
Lowest cost at scale: Apple Foundation Models 3 — Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.1's $1.25/$4.25 per 1M tokens.
Largest single-prompt input: Muse Spark 1.1 — Its 1M window is about 256× larger than Apple Foundation Models 3's 4K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Apple Foundation Models 3 — At Not published it undercuts Muse Spark 1.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Muse Spark 1.1 — Larger 1M window fits more in one prompt.
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 scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported): Muse Spark 1.1 — That is its strongest area.
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.
Muse Spark 1.1: where it fits
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Released July 9, 2026 by Meta, it is built for scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported), subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck, professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported), and managing its own context: it compacts the 1M window mid-run instead of relying on external windowing.
Its trade-offs: not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark, the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0, closed weights end the free, self-hostable Llama path — this is the first model Meta has charged for, and uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Apple Foundation Models 3 and Muse Spark 1.1 overlap enough that the right pick depends on your specific job. Apple Foundation Models 3 costs less per token; Muse Spark 1.1 holds the larger context; and each leads in its own area — Apple Foundation Models 3 for runs entirely on-device on iphone - no api call, no per-token cost, works offline, Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Apple Foundation Models 3 or Muse Spark 1.1 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 Muse Spark 1.1 leans toward scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Apple Foundation Models 3 or Muse Spark 1.1?
Apple Foundation Models 3 is cheaper — Not published vs $1.25/$4.25 per 1M tokens.
Which has the bigger context window?
Muse Spark 1.1 — 1M vs 4K, about 256× 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 Muse Spark 1.1 together?
Yes — a multi-model platform like LumiChats gives you Apple Foundation Models 3, Muse Spark 1.1 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 Muse Spark 1.1?
Muse Spark 1.1 — released July 9, 2026, about 38 days after Apple Foundation Models 3.
Apple Foundation Models 3 vs Muse Spark 1.1
Apple · US | Meta · US · 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 Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported) or subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck. On a tight budget at scale, Apple Foundation Models 3 is the value pick.
Apple Foundation Models 3 (Apple) and Muse Spark 1.1 (Meta) are two of the models people most often weigh against each other in 2026. 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. Muse Spark 1.1 is meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: Muse Spark 1.1 holds 256× more — 1M (~1,573 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: Muse Spark 1.1 is the newer model by about 38 days (released July 9, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Apple Foundation Models 3
Muse Spark 1.1
Provider
Apple (US)
Meta (US)
Released
June 2026
July 9, 2026
Context window
4K (~6 pages)
1M (~1,573 pages)
Price (in/out)
Not published
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
54.1%
Who wins what
Runs entirely on-device on iPhone - no API call, no per-token cost, works offline
Apple Foundation Models 3
Apple Foundation Models 3 lists runs entirely on-device on iPhone - no API call, no per-token cost, works offline among its strengths; Muse Spark 1.1 does not.
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; Muse Spark 1.1 does not.
Deep integration with iOS apps via the Foundation Models framework, now open to third-party LLM providers too
Apple Foundation Models 3
Muse Spark 1.1 is comparatively weak here — uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication
Scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported)
Muse Spark 1.1
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding — and it carries the larger 1M context.
Subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck
Muse Spark 1.1
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding — and it is the newer of the two.
Professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported)
Muse Spark 1.1
Muse Spark 1.1 lists professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported) among its strengths; Apple Foundation Models 3 does not.
Lowest cost at scale
Apple Foundation Models 3
Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.1's $1.25/$4.25 per 1M tokens.
Largest single-prompt input
Muse Spark 1.1
Its 1M window is about 256× larger than Apple Foundation Models 3's 4K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Apple Foundation Models 3
At Not published it undercuts Muse Spark 1.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Spark 1.1
Larger 1M window fits more in one prompt.
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 scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported)
→ Muse Spark 1.1
That is its strongest area.
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.
Muse Spark 1.1: where it fits
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Released July 9, 2026 by Meta, it is built for scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported), subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck, professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported), and managing its own context: it compacts the 1M window mid-run instead of relying on external windowing.
Its trade-offs: not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark, the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0, closed weights end the free, self-hostable Llama path — this is the first model Meta has charged for, and uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Apple Foundation Models 3 and Muse Spark 1.1 overlap enough that the right pick depends on your specific job. Apple Foundation Models 3 costs less per token; Muse Spark 1.1 holds the larger context; and each leads in its own area — Apple Foundation Models 3 for runs entirely on-device on iphone - no api call, no per-token cost, works offline, Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Apple Foundation Models 3 and Muse Spark 1.1 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 Muse Spark 1.1 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 Muse Spark 1.1 leans toward scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Apple Foundation Models 3 or Muse Spark 1.1?
Apple Foundation Models 3 is cheaper — Not published vs $1.25/$4.25 per 1M tokens.
Which has the bigger context window?
Muse Spark 1.1 — 1M vs 4K, about 256× 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 Muse Spark 1.1 together?
Yes — a multi-model platform like LumiChats gives you Apple Foundation Models 3, Muse Spark 1.1 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 Muse Spark 1.1?
Muse Spark 1.1 — released July 9, 2026, about 38 days after Apple Foundation Models 3.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.