Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Pick Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters or open weights under openmdw-1.1, shipped day one in bf16, fp8, nvfp4 and int4 across every major runtime. On a tight budget at scale, Gemma 4 is the value pick.
Gemma 4 (Google) and Laguna XS 2.1 (Poolside) 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. Laguna XS 2.1 is a 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: 256K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: Laguna XS 2.1 is the newer model by about 3 months (released July 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemma 4
Laguna XS 2.1
Provider
Google (US)
Poolside (US)
Released
April 2, 2026
July 2, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.1/$0.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
70.9%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Self-hosted, data-private deployment: Gemma 4 — Gemma 4 lists self-hosted, data-private deployment among its strengths; Laguna XS 2.1 does not.
Running locally or on edge devices: Gemma 4 — Gemma 4 lists running locally or on edge devices among its strengths; Laguna XS 2.1 does not.
Fine-tuning on your own data: Gemma 4 — Gemma 4 lists fine-tuning on your own data among its strengths; Laguna XS 2.1 does not.
Remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters: Laguna XS 2.1 — A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven — and it is the newer of the two.
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime: Laguna XS 2.1 — Laguna XS 2.1 lists open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime among its strengths; Gemma 4 does not.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price: Laguna XS 2.1 — Laguna XS 2.1 lists cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price among its strengths; Gemma 4 does not.
Lowest cost at scale: Gemma 4 — Its weights are open, so at volume you pay for your own hardware instead of Laguna XS 2.1's $0.1/$0.2 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Gemma 4 — At Open weight (self-host / free) it undercuts Laguna XS 2.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Laguna XS 2.1 — Larger 256K window fits more in one prompt.
Anyone whose priority is self-hosted, data-private deployment: Gemma 4 — It is specifically built for that.
Anyone whose priority is remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters: Laguna XS 2.1 — 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.
Laguna XS 2.1: where it fits
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. Released July 2, 2026 by Poolside, it is built for remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters, open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime, cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price, and unusually transparent evaluation — it publishes its harness, step limits, and sandbox specs.
Its trade-offs: weeks old with no independent replication; every published score traces back to Poolside's own harness, the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case, and weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise. At $0.1 in / $0.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Gemma 4 and Laguna XS 2.1 overlap enough that the right pick depends on your specific job. Gemma 4 costs less per token; Laguna XS 2.1 holds the larger context; and each leads in its own area — Gemma 4 for self-hosted, data-private deployment, Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Gemma 4 or Laguna XS 2.1 better for coding?
Public SWE-Bench figures are not available for Gemma 4, 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 Laguna XS 2.1 leans toward remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 or Laguna XS 2.1?
Gemma 4 is cheaper — Open weight (self-host / free) vs $0.1/$0.2 per 1M tokens.
Which has the bigger context window?
Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemma 4 and Laguna XS 2.1 together?
Yes — a multi-model platform like LumiChats gives you Gemma 4, Laguna XS 2.1 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 or Laguna XS 2.1?
Laguna XS 2.1 — released July 2, 2026, about 3 months after Gemma 4.
Gemma 4 vs Laguna XS 2.1
Google · US | Poolside · US · Updated June 2026
Quick verdict
Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Pick Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters or open weights under openmdw-1.1, shipped day one in bf16, fp8, nvfp4 and int4 across every major runtime. On a tight budget at scale, Gemma 4 is the value pick.
Gemma 4 (Google) and Laguna XS 2.1 (Poolside) 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. Laguna XS 2.1 is a 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: 256K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: Laguna XS 2.1 is the newer model by about 3 months (released July 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemma 4
Laguna XS 2.1
Provider
Google (US)
Poolside (US)
Released
April 2, 2026
July 2, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.1/$0.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
70.9%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Self-hosted, data-private deployment
Gemma 4
Gemma 4 lists self-hosted, data-private deployment among its strengths; Laguna XS 2.1 does not.
Running locally or on edge devices
Gemma 4
Gemma 4 lists running locally or on edge devices among its strengths; Laguna XS 2.1 does not.
Fine-tuning on your own data
Gemma 4
Gemma 4 lists fine-tuning on your own data among its strengths; Laguna XS 2.1 does not.
Remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters
Laguna XS 2.1
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven — and it is the newer of the two.
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime
Laguna XS 2.1
Laguna XS 2.1 lists open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime among its strengths; Gemma 4 does not.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price
Laguna XS 2.1
Laguna XS 2.1 lists cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price among its strengths; Gemma 4 does not.
Lowest cost at scale
Gemma 4
Its weights are open, so at volume you pay for your own hardware instead of Laguna XS 2.1's $0.1/$0.2 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemma 4
At Open weight (self-host / free) it undercuts Laguna XS 2.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Laguna XS 2.1
Larger 256K window fits more in one prompt.
Anyone whose priority is self-hosted, data-private deployment
→ Gemma 4
It is specifically built for that.
Anyone whose priority is remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters
→ Laguna XS 2.1
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.
Laguna XS 2.1: where it fits
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. Released July 2, 2026 by Poolside, it is built for remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters, open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime, cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price, and unusually transparent evaluation — it publishes its harness, step limits, and sandbox specs.
Its trade-offs: weeks old with no independent replication; every published score traces back to Poolside's own harness, the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case, and weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise. At $0.1 in / $0.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Gemma 4 and Laguna XS 2.1 overlap enough that the right pick depends on your specific job. Gemma 4 costs less per token; Laguna XS 2.1 holds the larger context; and each leads in its own area — Gemma 4 for self-hosted, data-private deployment, Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Gemma 4 and Laguna XS 2.1 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.
Public SWE-Bench figures are not available for Gemma 4, 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 Laguna XS 2.1 leans toward remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 or Laguna XS 2.1?
Gemma 4 is cheaper — Open weight (self-host / free) vs $0.1/$0.2 per 1M tokens.
Which has the bigger context window?
Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemma 4 and Laguna XS 2.1 together?
Yes — a multi-model platform like LumiChats gives you Gemma 4, Laguna XS 2.1 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 or Laguna XS 2.1?
Laguna XS 2.1 — released July 2, 2026, about 3 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.