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Model comparison

Holo3-122B-A10B vs Laguna XS.2

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
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No comparison
Poolside
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1 category wins0 category wins

Evidence parity. Holo3-122B-A10B and Laguna XS.2 share 0 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Holo3-122B-A10B; 5 to Laguna XS.2.

Updated July 27, 2026
Shared results
0
Holo3-122B-A10B only
1
Laguna XS.2 only
5
Comparable categories
1 / 8

Treat this as a split decision. Holo3-122B-A10B makes more sense if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model; Laguna XS.2 is the better fit if you want the cheaper token bill or you need the larger 256K context window.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Holo3-122B-A10B and Laguna XS.2 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

Holo3-122B-A10B is also the more expensive model on tokens at $0.40 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Laguna XS.2. That is roughly Infinityx on output cost alone. Laguna XS.2 is the reasoning model in the pair, while Holo3-122B-A10B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Laguna XS.2 gives you the larger context window at 256K, compared with 64K for Holo3-122B-A10B.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricHolo3-122B-A10BLaguna XS.2Comparison
Input / output priceUSD per 1M tokensHolo3-122B-A10B$0.4 input / $3 outputLaguna XS.2$0 input / $0 outputLaguna XS.2 has the lower combined listed price.
Generation speedtokens per secondHolo3-122B-A10BNot availableLaguna XS.2Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenHolo3-122B-A10BNot availableLaguna XS.2Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensHolo3-122B-A10B64KLaguna XS.2256KLaguna XS.2 lists the larger context window.

Benchmark Deep Dive

AgenticHolo3-122B-A10B wins
BenchmarkHolo3-122B-A10BLaguna XS.2Result
OSWorld-VerifiedSource 78.8%Not comparable
Terminal-Bench 2.0Source 35.7%Not comparable
Coding
BenchmarkHolo3-122B-A10BLaguna XS.2Result
SWE-bench VerifiedSource 69.9%Not comparable
SWE MultilingualSource 57.7%Not comparable
SWE-bench ProSource 46.3%Not comparable
Terminal-Bench 2.0Source 35.7%Not comparable
Frequently Asked Questions (2)

Which is better, Holo3-122B-A10B or Laguna XS.2?

Holo3-122B-A10B and Laguna XS.2 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for agentic tasks, Holo3-122B-A10B or Laguna XS.2?

Holo3-122B-A10B has the edge for agentic tasks in this comparison, averaging 78.9 versus 35.7. Laguna XS.2 stays close enough that the answer can still flip depending on your workload.

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Last updated: July 27, 2026

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