Pick Grok 4.5 for cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost or extreme token efficiency — around 4x fewer output tokens per task than opus 4.8. 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. Choose Laguna XS 2.1 if you need self-hosting or data privacy; Grok 4.5 if you want a managed API.
Grok 4.5 (xAI) and Laguna XS 2.1 (Poolside) are two of the models people most often weigh against each other in 2026. Grok 4.5 is xAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex. 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, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: Laguna XS 2.1 is about 20× cheaper on input ($0.1/$0.2 per 1M tokens vs $2/$6 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Grok 4.5 holds 1.9× more — 500K (~750 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.
Specifications
Spec
Grok 4.5
Laguna XS 2.1
Provider
xAI (US)
Poolside (US)
Released
July 8, 2026
July 2, 2026
Context window
500K (~750 pages)
256K (~393 pages)
Price (in/out)
$2/$6 per 1M tokens
$0.1/$0.2 per 1M tokens
Open weight?
No — API only
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
Cheap, token-efficient agentic coding — about GPT-5.5-Codex quality at roughly half the cost: Grok 4.5 — Its 500K window holds about 1.9× more than Laguna XS 2.1's 256K in a single prompt.
Extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8: Grok 4.5 — Laguna XS 2.1 is comparatively weak here — the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case
In-IDE coding, trained on real Cursor developer sessions and shipped natively in Cursor: Grok 4.5 — XAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex — and it carries the larger 500K context.
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 runs cheaper at $0.1/$0.2 per 1M tokens.
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime: Laguna XS 2.1 — Open weights make this possible at all — Grok 4.5 is API-only, so it cannot leave the vendor's servers.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price: Laguna XS 2.1 — At $0.1/$0.2 per 1M tokens it undercuts Grok 4.5 ($2/$6 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale: Laguna XS 2.1 — At $0.1/$0.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Grok 4.5 — Its 500K window is about 1.9× larger than Laguna XS 2.1's 256K, fitting roughly 750 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Laguna XS 2.1 — At $0.1/$0.2 per 1M tokens it undercuts Grok 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Grok 4.5 — Larger 500K window fits more in one prompt.
A team with data-privacy or self-hosting needs: Laguna XS 2.1 — Open weights let you run it on your own hardware; Grok 4.5 is API-only.
Anyone whose priority is cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost: Grok 4.5 — 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.
Grok 4.5: where it fits
XAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex. Released July 8, 2026 by xAI, it is built for cheap, token-efficient agentic coding — about GPT-5.5-Codex quality at roughly half the cost, extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8, in-IDE coding, trained on real Cursor developer sessions and shipped natively in Cursor, and top-tier placement on the Artificial Analysis Intelligence Index.
Its trade-offs are real: smaller 500K context (halved from the 1M generation), with pricing that doubles above 200K tokens, and eU launch delayed; no open weights. At $2 in / $6 out per million tokens, it sits in the mid price band.
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
The defining split here is open vs. closed. Laguna XS 2.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Grok 4.5 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 Grok 4.5 or Laguna XS 2.1 better for coding?
Public SWE-Bench figures are not available for Grok 4.5, so the honest test is your own repository — run an identical real bug through both. By design, Grok 4.5 leans toward cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost 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, Grok 4.5 or Laguna XS 2.1?
Laguna XS 2.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Grok 4.5 is API-metered at $2/$6 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?
Grok 4.5 — 500K vs 256K, about 1.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4.5 and Laguna XS 2.1 together?
Yes — a multi-model platform like LumiChats gives you Grok 4.5, 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, Grok 4.5 or Laguna XS 2.1?
Grok 4.5 — released July 8, 2026, about 6 days after Laguna XS 2.1.
Grok 4.5 vs Laguna XS 2.1
xAI · US | Poolside · US · Updated June 2026
Quick verdict
Pick Grok 4.5 for cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost or extreme token efficiency — around 4x fewer output tokens per task than opus 4.8. 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. Choose Laguna XS 2.1 if you need self-hosting or data privacy; Grok 4.5 if you want a managed API.
Grok 4.5 (xAI) and Laguna XS 2.1 (Poolside) are two of the models people most often weigh against each other in 2026. Grok 4.5 is xAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex. 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, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Laguna XS 2.1 is about 20× cheaper on input ($0.1/$0.2 per 1M tokens vs $2/$6 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Grok 4.5 holds 1.9× more — 500K (~750 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.
Side-by-side specs
Spec
Grok 4.5
Laguna XS 2.1
Provider
xAI (US)
Poolside (US)
Released
July 8, 2026
July 2, 2026
Context window
500K (~750 pages)
256K (~393 pages)
Price (in/out)
$2/$6 per 1M tokens
$0.1/$0.2 per 1M tokens
Open weight?
No — API only
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
Cheap, token-efficient agentic coding — about GPT-5.5-Codex quality at roughly half the cost
Grok 4.5
Its 500K window holds about 1.9× more than Laguna XS 2.1's 256K in a single prompt.
Extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8
Grok 4.5
Laguna XS 2.1 is comparatively weak here — the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case
In-IDE coding, trained on real Cursor developer sessions and shipped natively in Cursor
Grok 4.5
XAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex — and it carries the larger 500K context.
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 runs cheaper at $0.1/$0.2 per 1M tokens.
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime
Laguna XS 2.1
Open weights make this possible at all — Grok 4.5 is API-only, so it cannot leave the vendor's servers.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price
Laguna XS 2.1
At $0.1/$0.2 per 1M tokens it undercuts Grok 4.5 ($2/$6 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale
Laguna XS 2.1
At $0.1/$0.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Grok 4.5
Its 500K window is about 1.9× larger than Laguna XS 2.1's 256K, fitting roughly 750 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Laguna XS 2.1
At $0.1/$0.2 per 1M tokens it undercuts Grok 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Grok 4.5
Larger 500K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Laguna XS 2.1
Open weights let you run it on your own hardware; Grok 4.5 is API-only.
Anyone whose priority is cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost
→ Grok 4.5
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.
Grok 4.5: where it fits
XAI's first coding-focused model — pitched as Opus-class but faster, more token-efficient, and cheaper, undercutting GPT-5.5-Codex. Released July 8, 2026 by xAI, it is built for cheap, token-efficient agentic coding — about GPT-5.5-Codex quality at roughly half the cost, extreme token efficiency — around 4x fewer output tokens per task than Opus 4.8, in-IDE coding, trained on real Cursor developer sessions and shipped natively in Cursor, and top-tier placement on the Artificial Analysis Intelligence Index.
Its trade-offs are real: smaller 500K context (halved from the 1M generation), with pricing that doubles above 200K tokens, and eU launch delayed; no open weights. At $2 in / $6 out per million tokens, it sits in the mid price band.
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
The defining split here is open vs. closed. Laguna XS 2.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Grok 4.5 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 Grok 4.5 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 Grok 4.5, so the honest test is your own repository — run an identical real bug through both. By design, Grok 4.5 leans toward cheap, token-efficient agentic coding — about gpt-5.5-codex quality at roughly half the cost 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, Grok 4.5 or Laguna XS 2.1?
Laguna XS 2.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Grok 4.5 is API-metered at $2/$6 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?
Grok 4.5 — 500K vs 256K, about 1.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4.5 and Laguna XS 2.1 together?
Yes — a multi-model platform like LumiChats gives you Grok 4.5, 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, Grok 4.5 or Laguna XS 2.1?
Grok 4.5 — released July 8, 2026, about 6 days after Laguna XS 2.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.