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 GPT-5.4 for strong general-purpose default or coding and software engineering. Choose Gemma 4 26B A4B if you need self-hosting or data privacy; GPT-5.4 if you want a managed API.
Gemma 4 26B A4B (Google) and GPT-5.4 (OpenAI) 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. GPT-5.4 is openAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: Gemma 4 26B A4B is about 17× cheaper on input ($0.15/$0.6 per 1M tokens vs $2.5/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: GPT-5.4 holds 3.8× more — 1M (~1,500 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: Gemma 4 26B A4B is the newer model by about 28 days (released April 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemma 4 26B A4B
GPT-5.4
Provider
Google (US)
OpenAI (US)
Released
April 2, 2026
March 5, 2026
Context window
256K (~393 pages)
1M (~1,500 pages)
Price (in/out)
$0.15/$0.6 per 1M tokens
$2.5/$15 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, image, video, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total): Gemma 4 26B A4B — A core design strength of Gemma 4 26B A4B.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost: Gemma 4 26B A4B — A core design strength of Gemma 4 26B A4B.
Strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6): Gemma 4 26B A4B — A core design strength of Gemma 4 26B A4B.
Strong general-purpose default: GPT-5.4 — A core design strength of GPT-5.4.
Coding and software engineering: GPT-5.4 — A core design strength of GPT-5.4.
Document understanding and tool use: GPT-5.4 — A core design strength of GPT-5.4.
Lowest cost at scale: Gemma 4 26B A4B — At $0.15/$0.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GPT-5.4 — Its 1M window is about 3.8× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Gemma 4 26B A4B — At $0.15/$0.6 per 1M tokens it undercuts GPT-5.4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-5.4 — 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; GPT-5.4 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 strong general-purpose default: GPT-5.4 — 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 $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
GPT-5.4: where it fits
OpenAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. Released March 5, 2026 by OpenAI, it is built for strong general-purpose default, coding and software engineering, document understanding and tool use, and 1M context with good token efficiency.
Its trade-offs: topped by GPT-5.5 on the hardest tasks, and pricier than open-weight rivals. At $2.5 in / $15 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. GPT-5.4 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 26B A4B or GPT-5.4 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, Gemma 4 26B A4B leans toward fast, cheap inference from a sparse moe (3.8b active of 25.2b total) while GPT-5.4 leans toward strong general-purpose default, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 26B A4B or GPT-5.4?
Gemma 4 26B A4B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.4 is API-metered at $2.5/$15 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?
GPT-5.4 — 1M vs 256K, about 3.8× 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 GPT-5.4 together?
Yes — a multi-model platform like LumiChats gives you Gemma 4 26B A4B, GPT-5.4 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, Gemma 4 26B A4B or GPT-5.4?
Gemma 4 26B A4B — released April 2, 2026, about 28 days after GPT-5.4.
Gemma 4 26B A4B vs GPT-5.4
Google · US | OpenAI · 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 GPT-5.4 for strong general-purpose default or coding and software engineering. Choose Gemma 4 26B A4B if you need self-hosting or data privacy; GPT-5.4 if you want a managed API.
Gemma 4 26B A4B (Google) and GPT-5.4 (OpenAI) 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. GPT-5.4 is openAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. 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 17× cheaper on input ($0.15/$0.6 per 1M tokens vs $2.5/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: GPT-5.4 holds 3.8× more — 1M (~1,500 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: Gemma 4 26B A4B is the newer model by about 28 days (released April 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemma 4 26B A4B
GPT-5.4
Provider
Google (US)
OpenAI (US)
Released
April 2, 2026
March 5, 2026
Context window
256K (~393 pages)
1M (~1,500 pages)
Price (in/out)
$0.15/$0.6 per 1M tokens
$2.5/$15 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, image, video, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total)
Gemma 4 26B A4B
A core design strength of Gemma 4 26B A4B.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost
At $0.15/$0.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GPT-5.4
Its 1M window is about 3.8× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemma 4 26B A4B
At $0.15/$0.6 per 1M tokens it undercuts GPT-5.4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-5.4
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; GPT-5.4 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 strong general-purpose default
→ GPT-5.4
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 $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
GPT-5.4: where it fits
OpenAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. Released March 5, 2026 by OpenAI, it is built for strong general-purpose default, coding and software engineering, document understanding and tool use, and 1M context with good token efficiency.
Its trade-offs: topped by GPT-5.5 on the hardest tasks, and pricier than open-weight rivals. At $2.5 in / $15 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. GPT-5.4 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 GPT-5.4 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.
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 GPT-5.4 leans toward strong general-purpose default, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 26B A4B or GPT-5.4?
Gemma 4 26B A4B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.4 is API-metered at $2.5/$15 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?
GPT-5.4 — 1M vs 256K, about 3.8× 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 GPT-5.4 together?
Yes — a multi-model platform like LumiChats gives you Gemma 4 26B A4B, GPT-5.4 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, Gemma 4 26B A4B or GPT-5.4?
Gemma 4 26B A4B — released April 2, 2026, about 28 days after GPT-5.4.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.