Model comparison
DeepSeek V3.2 vs Laguna XS.2
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3.2 #88 (Supported); Laguna XS.2 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 and Laguna XS.2 share 0 comparable benchmark results. 1 of 8 categories are comparable. 19 results are unique to DeepSeek V3.2; 5 to Laguna XS.2.
Updated July 27, 2026- Shared results
- 0
- DeepSeek V3.2 only
- 19
- Laguna XS.2 only
- 5
- Comparable categories
- 1 / 8
Treat this as a split decision. DeepSeek V3.2 makes more sense if coding 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
DeepSeek V3.2 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.
DeepSeek V3.2 is also the more expensive model on tokens at $0.28 input / $0.42 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 DeepSeek V3.2 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 128K for DeepSeek V3.2.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 | Laguna XS.2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2$0.28 input / $0.42 output | Laguna XS.2$0 input / $0 output | Laguna XS.2 has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3.235 tok/s | Laguna XS.2Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3.23.75 s | Laguna XS.2Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3.2128K | Laguna XS.2256K | Laguna XS.2 lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
CodingDeepSeek V3.2 wins7 benchmarks
| Benchmark | DeepSeek V3.2 | Laguna XS.2 | Result |
|---|---|---|---|
| SWE-RebenchSource | 60.9% | — | Not comparable |
| React Native EvalsSource | 71.5% | — | Not comparable |
| AA-SciCodeSource | 38.7% | — | Not comparable |
| 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 |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | DeepSeek V3.2 | Laguna XS.2 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | — | Not comparable |
| AA-GPQA DiamondSource | 75.1% | — | Not comparable |
| AA-HLESource | 10.5% | — | Not comparable |
| AA-Omniscience IndexSource | -46.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 24.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 93.5% | — | Not comparable |
Math2 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V3.2 | Laguna XS.2 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1200 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V3.2 | Laguna XS.2 | Result |
|---|---|---|---|
| AA-IFBenchSource | 49.0% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, DeepSeek V3.2 or Laguna XS.2?
DeepSeek V3.2 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 coding, DeepSeek V3.2 or Laguna XS.2?
DeepSeek V3.2 has the edge for coding in this comparison, averaging 60.9 versus 60.8. Laguna XS.2 stays close enough that the answer can still flip depending on your workload.
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