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© 2026 CompareLLM. Public benchmark data aggregated from Arena Elo, LiveBench, SWE-bench & OpenRouter.

Every score has a dated snapshot.

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  2. Comparisons
  3. Poolside: Laguna XS 2.1 vs OpenAI: o3 Mini

Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Poolside: Laguna XS 2.1 vs OpenAI: o3 Mini benchmark

In this head-to-head showdown, Poolside: Laguna XS 2.1 is more budget-friendly at $0.12/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Executive Comparison Verdict

Bottom Line: Both Poolside: Laguna XS 2.1 and OpenAI: o3 Mini present distinct architectural strengths. Compare the verified benchmark matrix below to choose the model tailored to your specific application requirements.
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Executive Verdict Summary

Poolside: Laguna XS 2.1 holds empirical advantage (3 of 3 metrics)

Coding / SWESWE-bench
OpenAI: o3 MiniTop code solve rate
ReasoningGPQA / Live
OpenAI: o3 MiniTop logical accuracy
Best Value$/1M Tok
Poolside: Laguna XS 2.1Lowest API billing cost
Speed / TokTok/Sec
OpenAI: o3 MiniFastest stream rate

Verified Advantage Breakdown

3 benchmarks evaluated across capability, speed, and cost

Poolside: Laguna XS 2.1 (3)OpenAI: o3 Mini (0)
Poolside: Laguna XS 2.1
3 of 3 Wins
✓Input price✓Output price✓Context window
OpenAI: o3 Mini
0 of 3 Wins
Competitive baseline across remaining benchmarks
poolside
Leads 3 of 3
Poolside: Laguna XS 2.1

Auto-discovered from OpenRouter (poolside/laguna-xs-2.1). Preview until a second source matches.

In: $0.06 · Out: $0.12/1M
OpenAI
OpenAI: o3 Mini

Auto-discovered from OpenRouter (openai/o3-mini). Preview until a second source matches.

o3-miniElo 1,560In: $1.1 · Out: $4.4/1M

OpenAI: o3 Mini Thinking Depth & Cost Scaler

Model B

Simulate accuracy gains vs added response time & token cost

Mode: Medium (Standard)

Reasoning models “think before answering” by generating internal reasoning tokens. Higher effort improves math, coding, and logic accuracy, but increases response delay and token costs.

Delay
290 ms
Standard
CoT Tokens
~1,500
Internal reasoning
Cost / 1k
$8.47
4.5× base bill
Accuracy Boost
+4.5%
STEM & Logic
Top Rival Showdowns for Poolside: Laguna XS 2.1
All Matchups
Compare vs:vs Claude Opus 4.5vs GPT-5vs Gemini 3 Provs Grok 4.6vs DeepSeek V4 Pro
Preference Leader

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar LeaderPoolside: Laguna XS 2.1 Wins

Poolside: Laguna XS 2.1

$0.12 / 1M output

Capability Percentiles

Relative percentile scores computed across all active models in the benchmark catalog.

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top standard models across 6 key capability dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect
0–100 %ile

Overall Matchup Breakdown

Category wins across reasoning intelligence, generation speed, and token cost.

Poolside: Laguna XS 2.1 (3)vsOpenAI: o3 Mini (7)
Poolside: Laguna XS 2.1: 3W (30%)Overall: OpenAI: o3 MiniOpenAI: o3 Mini: 7W (70%)
← Poolside: Laguna XS 2.1OpenAI: o3 Mini →
🏆OpenAI: o3 Mini Leads(5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Benchmark
Poolside: Laguna XS 2.1vsOpenAI: o3 Mini
Preference Elo
—vs1,560
Coding Elo
—vs1,585
SWE-bench
—vs78.5%
LiveBench
—vs72.4%
GPQA Diamond
—vs87.2%
Poolside: Laguna XS 2.1: 0WOpenAI: o3 Mini: 5W
🏆OpenAI: o3 Mini Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark
Poolside: Laguna XS 2.1vsOpenAI: o3 Mini
Output speed
—vs92 tok/s
Time to first token
—vs290 ms
Poolside: Laguna XS 2.1: 0WOpenAI: o3 Mini: 2W
🏆Poolside: Laguna XS 2.1 Leads(3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark
Poolside: Laguna XS 2.1vsOpenAI: o3 Mini
Output price
$0.12/1Mvs$4.4/1M+$4.28/1M
Input price
$0.06/1Mvs$1.1/1M+$1.04/1M
Context window
262kvs200k+62k
Poolside: Laguna XS 2.1: 3WOpenAI: o3 Mini: 0W

Side-by-Side Benchmark Matrix

Poolside: Laguna XS 2.1OpenAI: o3 Mini
Preference Elo
Poolside: Laguna XS 2.1—
OpenAI: o3 Mini1,560
Coding Elo
Poolside: Laguna XS 2.1—
OpenAI: o3 Mini1,585
LiveBench
Poolside: Laguna XS 2.1—
OpenAI: o3 Mini72.4%
SWE-bench
Poolside: Laguna XS 2.1—
OpenAI: o3 Mini78.5%
GPQA Diamond
Poolside: Laguna XS 2.1—
OpenAI: o3 Mini87.2%
Time to first token
Poolside: Laguna XS 2.1—
OpenAI: o3 Mini290 ms
Output speed
Poolside: Laguna XS 2.1—
OpenAI: o3 Mini92 tok/s
Input pricePoolside: Laguna XS 2.1 +$1.04/1M
Poolside: Laguna XS 2.1$0.06/1M
OpenAI: o3 Mini$1.1/1M
Output pricePoolside: Laguna XS 2.1 +$4.28/1M
Poolside: Laguna XS 2.1$0.12/1M
OpenAI: o3 Mini$4.4/1M
Context windowPoolside: Laguna XS 2.1 +62k
Poolside: Laguna XS 2.1262k
OpenAI: o3 Mini200k
BenchmarkPoolside: Laguna XS 2.1OpenAI: o3 MiniAdvantage Delta
Preference Elo—
1,560
lmarena · Aug 17, 2026
—
Coding Elo—
1,585
lmarena · Aug 17, 2026
—
LiveBench—
72.4%
livebench · Aug 17, 2026
—
SWE-bench—
78.5%
swebench · Aug 17, 2026
—
GPQA Diamond—
87.2%
seed-bootstrap · Aug 1, 2026
—
Time to first token—
290 ms
seed-bootstrap · Aug 1, 2026
—
Output speed—
92 tok/s
seed-bootstrap · Aug 1, 2026
—
Input price
$0.06/1M
openrouter · Aug 17, 2026
$1.1/1M
openrouter · Aug 17, 2026
+$1.04/1M
Output price
$0.12/1M
openrouter · Aug 17, 2026
$4.4/1M
openrouter · Aug 17, 2026
+$4.28/1M
Context window
262k
openrouter · Aug 17, 2026
200k
openrouter · Aug 17, 2026
+62k

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save 96% with Poolside: Laguna XS 2.1
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Poolside: Laguna XS 2.1$3.90 / mo
In: $2.1Out: $1.8
OpenAI: o3 Mini$104.50 / mo
In: $38.5Out: $66
Estimated Cost Delta

Poolside: Laguna XS 2.1 is estimated to save $100.60/month ($1,207/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    Poolside: Laguna XS 2.1:Pick Poolside: Laguna XS 2.1 when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatPoolside: Laguna XS 2.1

Lower output list price ($0.12/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGPoolside: Laguna XS 2.1

Larger window (262k).

Screenshots / visionOpenAI: o3 Mini

OpenAI: o3 Mini is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatPoolside: Laguna XS 2.1Lower output list price ($0.12/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGPoolside: Laguna XS 2.1Larger window (262k).
Screenshots / visionOpenAI: o3 MiniOpenAI: o3 Mini is the side marked multimodal in the catalog.

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK
VS
poolside

Poolside: Laguna XS 2.1

Elo n/a
SWE-bench—
Speed (tok/s)262k
Input / 1M Tokens$0.06/1M
Output / 1M Tokens$0.12/1M
OpenAI

OpenAI: o3 Mini

Elo 1,560
SWE-bench78.5%
Speed (tok/s)92 tok/s
Input / 1M Tokens$1.1/1M
Output / 1M Tokens$4.4/1M

Frequently Asked Questions

Which is better overall, Poolside: Laguna XS 2.1 or OpenAI: o3 Mini?
We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Poolside: Laguna XS 2.1 or OpenAI: o3 Mini?
SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?
Poolside: Laguna XS 2.1 output tokens are $0.12/1M versus $4.4/1M. Input prices and retry rates still move the real bill.
Which is faster, Poolside: Laguna XS 2.1 or OpenAI: o3 Mini?
We do not have TTFT for both models.
Which has the larger context window?
Poolside: Laguna XS 2.1 accepts 262k tokens versus 200k.
Can I self-host either model?
Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?
No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?
Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Poolside: Laguna XS 2.1 and OpenAI: o3 Mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Poolside: Laguna XS 2.1 matchups →|All OpenAI: o3 Mini matchups →
OpenAI: o3 Mini vs OpenAI o1-mini (previous gpt-mini)OpenAI: o3 Mini vs GPT-5 mini (next gpt-mini)GPT-5 vs OpenAI: o3 MiniGPT-4.5 Orion vs OpenAI: o3 MiniGPT-5.6 Sol vs OpenAI: o3 MiniGPT-5.6 Terra vs OpenAI: o3 Mini