Model comparison
GPT-5.4 nano vs Laguna S 2.1
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.4 nano #25 (Supported); Laguna S 2.1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.4 nano and Laguna S 2.1 share 1 comparable benchmark result. 1 of 8 categories are comparable. 28 results are unique to GPT-5.4 nano; 5 to Laguna S 2.1.
Updated July 21, 2026- Shared results
- 1
- GPT-5.4 nano only
- 28
- Laguna S 2.1 only
- 5
- Comparable categories
- 1 / 8
Treat this as a split decision. GPT-5.4 nano makes more sense if its workflow fits your team better; Laguna S 2.1 is the better fit if agentic is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.4 nano and Laguna S 2.1 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.
GPT-5.4 nano is also the more expensive model on tokens at $0.20 input / $1.25 output per 1M tokens, versus $0.10 input / $0.20 output per 1M tokens for Laguna S 2.1. That is roughly 6.3x on output cost alone. Laguna S 2.1 gives you the larger context window at 1M, compared with 400K for GPT-5.4 nano.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-5.4 nano | Δ | Laguna S 2.1 |
|---|---|---|---|
| Agentic | GPT-5.4 nano42.9 | Margin→ 27.3 | Laguna S 2.170.2 |
| Coding | GPT-5.4 nanoNot measured | MarginNo overlap | Laguna S 2.159.4 |
| Knowledge | GPT-5.4 nano43.8 | MarginNo overlap | Laguna S 2.1Not measured |
| Math | GPT-5.4 nano21.0 | MarginNo overlap | Laguna S 2.1Not measured |
| Multimodal | GPT-5.4 nano66.1 | MarginNo overlap | Laguna S 2.1Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 46.3%B 70.2%Winner: Laguna S 2.1Δ 23.9Terminal-Bench 2.0: GPT-5.4 nano scored 46.3%; Laguna S 2.1 scored 70.2%. Laguna S 2.1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.4 nano | Laguna S 2.1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.4 nano$0.2 input / $1.25 output | Laguna S 2.1$0.1 input / $0.2 output | Laguna S 2.1 has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.4 nano191 tok/s | Laguna S 2.1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.4 nano3.64 s | Laguna S 2.1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.4 nano400K | Laguna S 2.11M | Laguna S 2.1 lists the larger context window. |
Benchmark Deep Dive
AgenticLaguna S 2.1 wins10 benchmarks
| Benchmark | GPT-5.4 nano | Laguna S 2.1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 46.3% | 70.2% | Laguna S 2.1 leads |
| OSWorld-VerifiedSource | 39% | — | Not comparable |
| MCP AtlasSource | 56.1% | — | Not comparable |
| ToolathlonSource | 35.5% | — | Not comparable |
| τ²-bench resultsSource | 76% | — | Not comparable |
| AA Agentic IndexSource | 27.5% | — | Not comparable |
| APEX-Agents-AASource | 24.9% | — | Not comparable |
| GDPval-AASource | 30.0% | — | Not comparable |
| GDPval-AASource | 1100 | — | Not comparable |
| Toolathlon-VerifiedSource | — | 49.7% | Not comparable |
Coding7 benchmarks
| Benchmark | GPT-5.4 nano | Laguna S 2.1 | Result |
|---|---|---|---|
| Vibe Code BenchSource | 26.10% | — | Not comparable |
| AA Coding IndexSource | 56.1% | — | Not comparable |
| AA-SciCodeSource | 46.9% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 70.2% | Not comparable |
| SWE MultilingualSource | — | 78.5% | Not comparable |
| SWE-bench ProSource | — | 59.4% | Not comparable |
| deepSweSource | — | 40.4% | Not comparable |
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | GPT-5.4 nano | Laguna S 2.1 | Result |
|---|---|---|---|
| GPQASource | 82.8% | — | Not comparable |
| HLESource | 37.7% | — | Not comparable |
| HLE w/o toolsSource | 24.3% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 38.2% | — | Not comparable |
| AA-GPQA DiamondSource | 81.7% | — | Not comparable |
| AA-HLESource | 26.5% | — | Not comparable |
| AA-Omniscience IndexSource | -29.5% | — | Not comparable |
| AA-Omniscience AccuracySource | 25.4% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 73.6% | — | Not comparable |
Math2 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.4 nano | Laguna S 2.1 | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.9% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, GPT-5.4 nano or Laguna S 2.1?
GPT-5.4 nano and Laguna S 2.1 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, GPT-5.4 nano or Laguna S 2.1?
Laguna S 2.1 has the edge for agentic tasks in this comparison, averaging 70.2 versus 42.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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