Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Pick Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 or deepswe v1.1 long-horizon software engineering (75.4). Choose Gemma 4 if you need self-hosting or data privacy; Muse Spark 1.3 if you want a managed API.
Gemma 4 (Google) and Muse Spark 1.3 (Meta) are two of the models people most often weigh against each other in 2026. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Muse Spark 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Gemma 4 ships open weights you can self-host (hardware cost only, no per-token fee), while Muse Spark 1.3 is API-metered at $1.25/$4.25 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: Muse Spark 1.3 holds 3.9× more — 1M tokens (~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: Muse Spark 1.3 is the newer model by about 5 months (released September 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemma 4
Muse Spark 1.3
Provider
Google (US)
Meta (US)
Released
April 2, 2026
September 2, 2026
Context window
256K (~384 pages)
1M tokens (~1,500 pages)
Price (in/out)
Open weight (self-host / free)
$1.25/$4.25 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, image, code
text, image, video
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
98.1%
Who wins what
Self-hosted, data-private deployment: Gemma 4 — Open weights make this possible at all — Muse Spark 1.3 is API-only, so it cannot leave the vendor's servers.
Running locally or on edge devices: Gemma 4 — Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting — and its weights are open while Muse Spark 1.3 is API-only.
Fine-tuning on your own data: Gemma 4 — Gemma 4 lists fine-tuning on your own data among its strengths; Muse Spark 1.3 does not.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2: Muse Spark 1.3 — Its 1M tokens window holds about 3.9× more than Gemma 4's 256K in a single prompt.
DeepSWE v1.1 long-horizon software engineering (75.4): Muse Spark 1.3 — Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it carries the larger 1M tokens context.
Near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1): Muse Spark 1.3 — Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it is the newer of the two.
Lowest cost at scale: Gemma 4 — Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.3's $1.25/$4.25 per 1M tokens.
Largest single-prompt input: Muse Spark 1.3 — Its 1M tokens 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 Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Muse Spark 1.3 — Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs: Gemma 4 — Open weights let you run it on your own hardware; Muse Spark 1.3 is API-only.
Anyone whose priority is self-hosted, data-private deployment: Gemma 4 — It is specifically built for that.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2: Muse Spark 1.3 — That is its strongest area.
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 are real: 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.
Muse Spark 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. Gemma 4 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Muse Spark 1.3 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 Gemma 4 or Muse Spark 1.3 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, Gemma 4 leans toward self-hosted, data-private deployment while Muse Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 or Muse Spark 1.3?
Gemma 4 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Muse Spark 1.3 is API-metered at $1.25/$4.25 per 1M tokens. 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?
Muse Spark 1.3 — 1M tokens 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 Gemma 4 and Muse Spark 1.3 together?
Yes — a multi-model platform like LumiChats gives you Gemma 4, Muse Spark 1.3 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, Gemma 4 or Muse Spark 1.3?
Muse Spark 1.3 — released September 2, 2026, about 5 months after Gemma 4.
Gemma 4 vs Muse Spark 1.3
Google · US | Meta · US · Updated June 2026
Quick verdict
Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Pick Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 or deepswe v1.1 long-horizon software engineering (75.4). Choose Gemma 4 if you need self-hosting or data privacy; Muse Spark 1.3 if you want a managed API.
Gemma 4 (Google) and Muse Spark 1.3 (Meta) are two of the models people most often weigh against each other in 2026. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Muse Spark 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. 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: Gemma 4 ships open weights you can self-host (hardware cost only, no per-token fee), while Muse Spark 1.3 is API-metered at $1.25/$4.25 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: Muse Spark 1.3 holds 3.9× more — 1M tokens (~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: Muse Spark 1.3 is the newer model by about 5 months (released September 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemma 4
Muse Spark 1.3
Provider
Google (US)
Meta (US)
Released
April 2, 2026
September 2, 2026
Context window
256K (~384 pages)
1M tokens (~1,500 pages)
Price (in/out)
Open weight (self-host / free)
$1.25/$4.25 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, image, code
text, image, video
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
98.1%
Who wins what
Self-hosted, data-private deployment
Gemma 4
Open weights make this possible at all — Muse Spark 1.3 is API-only, so it cannot leave the vendor's servers.
Running locally or on edge devices
Gemma 4
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting — and its weights are open while Muse Spark 1.3 is API-only.
Fine-tuning on your own data
Gemma 4
Gemma 4 lists fine-tuning on your own data among its strengths; Muse Spark 1.3 does not.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2
Muse Spark 1.3
Its 1M tokens window holds about 3.9× more than Gemma 4's 256K in a single prompt.
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it carries the larger 1M tokens context.
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it is the newer of the two.
Lowest cost at scale
Gemma 4
Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.3's $1.25/$4.25 per 1M tokens.
Largest single-prompt input
Muse Spark 1.3
Its 1M tokens 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 Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Spark 1.3
Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Gemma 4
Open weights let you run it on your own hardware; Muse Spark 1.3 is API-only.
Anyone whose priority is self-hosted, data-private deployment
→ Gemma 4
It is specifically built for that.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2
→ Muse Spark 1.3
That is its strongest area.
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 are real: 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.
Muse Spark 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. Gemma 4 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Muse Spark 1.3 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 Gemma 4 and Muse Spark 1.3 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, Gemma 4 leans toward self-hosted, data-private deployment while Muse Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 or Muse Spark 1.3?
Gemma 4 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Muse Spark 1.3 is API-metered at $1.25/$4.25 per 1M tokens. 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?
Muse Spark 1.3 — 1M tokens 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 Gemma 4 and Muse Spark 1.3 together?
Yes — a multi-model platform like LumiChats gives you Gemma 4, Muse Spark 1.3 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, Gemma 4 or Muse Spark 1.3?
Muse Spark 1.3 — released September 2, 2026, about 5 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.