Gemma 4 26B A4B vs Muse Spark 1.1

Google · US | Meta · US · Updated June 2026

Quick verdict

Pick Gemma 4 26B A4B for fast, cheap inference from a sparse moe (3.8b active of 25.2b total) or near-31b-dense quality at a fraction of the compute and memory-bandwidth cost. 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. Choose Gemma 4 26B A4B if you need self-hosting or data privacy; Muse Spark 1.1 if you want a managed API.

Gemma 4 26B A4B (Google) and Muse Spark 1.1 (Meta) are two of the models people most often weigh against each other in 2026. Gemma 4 26B A4B is an Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. 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, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

▸Price: Gemma 4 26B A4B is about 10× cheaper on input ($0.12/$0.37 per 1M tokens vs $1.25/$4.25 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Muse Spark 1.1 holds 4× more — 1M (~1,573 pages) vs 256K (~393 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 3 months (released July 9, 2026), usually meaning fresher training data and capabilities.

Side-by-side specs

Spec	Gemma 4 26B A4B	Muse Spark 1.1
Provider	Google (US)	Meta (US)
Released	April 2, 2026	July 9, 2026
Context window	256K (~393 pages)	1M (~1,573 pages)
Price (in/out)	$0.12/$0.37 per 1M tokens	$1.25/$4.25 per 1M tokens
Open weight?	Yes — self-hostable	No — API only
Modalities	text, image, video, code	text, image, video, code
SWE-Bench Verified	Not published	Not published
MRCR v2 @ 1M	Not published	54.1%

Who wins what

Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total)

Gemma 4 26B A4B

At $0.12/$0.37 per 1M tokens it undercuts Muse Spark 1.1 ($1.25/$4.25 per 1M tokens), and that gap compounds at volume.

Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost

Gemma 4 26B A4B

An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost — and it runs cheaper at $0.12/$0.37 per 1M tokens.

Strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6)

Gemma 4 26B A4B

Muse Spark 1.1 is comparatively weak here — 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

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

Gemma 4 26B A4B is comparatively weak here — 256K context trails 1M-token frontier rivals, and this variant has no audio input (audio is E2B/E4B/12B only)

Lowest cost at scale

Gemma 4 26B A4B

At $0.12/$0.37 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

Muse Spark 1.1

Its 1M window is about 4× larger than Gemma 4 26B A4B's 256K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Gemma 4 26B A4B

At $0.12/$0.37 per 1M tokens 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.

A team with data-privacy or self-hosting needs

→ Gemma 4 26B A4B

Open weights let you run it on your own hardware; Muse Spark 1.1 is API-only.

Anyone whose priority is fast, cheap inference from a sparse moe (3.8b active of 25.2b total)

→ Gemma 4 26B A4B

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.

Gemma 4 26B A4B: where it fits

An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. Released April 2, 2026 by Google, it is built for fast, cheap inference from a sparse MoE (3.8B active of 25.2B total), near-31B-dense quality at a fraction of the compute and memory-bandwidth cost, strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6), and multimodal input (text/image, plus video processed as frames up to 60s) with native function calling.

Its trade-offs are real: all 25.2B parameters must be loaded into memory even though only 3.8B are active per token, and 256K context trails 1M-token frontier rivals, and this variant has no audio input (audio is E2B/E4B/12B only). At $0.12 in / $0.37 out per million tokens, it sits in the budget price band.

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

The defining split here is open vs. closed. Gemma 4 26B A4B gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Muse Spark 1.1 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 26B A4B 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.

See pricing

Frequently asked questions

Is Gemma 4 26B A4B 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, Gemma 4 26B A4B leans toward fast, cheap inference from a sparse moe (3.8b active of 25.2b total) 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, Gemma 4 26B A4B or Muse Spark 1.1?

Gemma 4 26B A4B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Muse Spark 1.1 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 1.1 — 1M vs 256K, about 4× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Gemma 4 26B A4B and Muse Spark 1.1 together?

Yes — a multi-model platform like LumiChats gives you Gemma 4 26B A4B, 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, Gemma 4 26B A4B or Muse Spark 1.1?

Muse Spark 1.1 — released July 9, 2026, about 3 months after Gemma 4 26B A4B.

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Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.