Laguna XS 2.1 vs Gemini 4 Argon
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Laguna XS 2.1 by Poolside against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.
Cambia e Confronta Qualsiasi Modello
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Live comparison: no in-depth editorial review has been published for this pair yet.
Laguna XS 2.1
Leader in Programmazione e CodiceLaguna XS 2.1 di Poolside è un modello di IA progettato per l’ingegneria del software autonoma, il refactoring multi-file e il debug avanzato, con finestra di contesto da 262K, velocità di 165 token/s, indice di intelligenza di 77/100 e tar
$0.05 / 1M
$0.20 / 1M
262.1K tokens
N/A
Gemini 4 Argon
IA Multimodale NativaGemini 4 Argon di Google è un modello di IA progettato per la comprensione multimodale nativa di testo e immagini e l’analisi visiva dei documenti, con finestra di contesto da 1M, velocità di 115 token/s, indice di intelligenza di 97/100 e
$2.00 / 1M
$10.00 / 1M
1M tokens
81.9%
Differenze Chiave a Colpo d’Occhio
- Laguna XS 2.1 is 46.3x cheaper for API usage (input + output tokens combined).
- Gemini 4 Argon has a larger context window (1M vs 262K tokens).
- Laguna XS 2.1 is faster at 165 tok/s vs 115 tok/s.
| Feature | Laguna XS 2.1 | Gemini 4 Argon |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 77 | 97 |
Provider | Poolside | |
Input Price Cost per million input tokens | $0.05 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $0.20 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.03 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 262.1K tokens~393 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 8K | 1000K |
Throughput Speed Tokens generated per second | 165 tok/s | 115 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 81.9% |
GPQA Diamond Graduate-level reasoning | N/A | 81.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.01 / 1M | $0.10 / 1M |
Chi vince in ogni categoria?
At-a-glance decision frameworkEvaluations ongoing
Punteggi Benchmark Verificati
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latenza e Tempo di Risposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulatore Interattivo dei Costi Token
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Laguna XS 2.1 · Strengths & Key Advantages
- Finestra di contesto da 262K con capacità massima di output fino a 8K token (MMLU-Pro 74% · Arena Elo 1280)
- Throughput elevato di 165 token/secondo con latenza al primo token (TTFT) di soli 240 ms
- Economia API competitiva ($0.05/$0.2 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
- Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
- Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità
Gemini 4 Argon · Strengths & Key Advantages
- Finestra di contesto da 1M con capacità massima di output fino a 1M token (SWE-bench Verified 81.9% · GPQA Diamond 81.5%)
- Throughput elevato di 115 token/secondo con latenza al primo token (TTFT) di soli 850 ms
- Economia API competitiva ($2/$10 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
- Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
- Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Laguna XS 2.1 | Gemini 4 Argon |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.01 | $2.45 |
Output Tokens / Task Tokens generated per task | 12K | 75K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 36K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | Laguna XS 2.1 | Gemini 4 Argon |
|---|---|---|
| Official API Model ID (SDK) | laguna-xs-2-1 | models/gemini-4-argon |
| API Protocol | Poolside REST API (OpenAI-Compatible) | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2026-07 | 2026-09 |
| Knowledge Cutoff | May 2026 | June 2026 |
| Architecture | Ultra-Fast Code Optimization Transformer | Pathways Multimodal Sparse Mixture-of-Experts |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.05/1M in) across full 262K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.005/1M tokens | Implicit + Explicit Context Caching at $0.1/1M with configurable TTL |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Vertex AI Supervised Adapter Tuning & Context Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Poolside Production Safety & Alignment Verified | Google DeepMind Frontier Safety Framework Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision, audio, video |
| Output Modalities | text | text |
Laguna XS 2.1 vs Gemini 4 Argon: Risposte Rapide (FAQ)
Which is more intelligent, Laguna XS 2.1 or Gemini 4 Argon?
Gemini 4 Argon is more intelligent. It scores 97 compared with 77 on the composite Intelligence Index.
Which model is faster?
Laguna XS 2.1 is faster, generating 165 tokens per second compared with 115 tokens per second.
Which model is cheaper to run?
Laguna XS 2.1 is cheaper at $0.03 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Laguna XS 2.1 has lower latency, with a time to first token of 0.24s compared with 0.85s.
Which model has a larger context window?
Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 262.1K tokens.
Verdetto
Choose Laguna XS 2.1 for ideale per l’ingegneria del software autonoma, il refactoring multi-file e il debug avanzato, sistemi rag aziendali e integrazioni api scalabili., or choose Gemini 4 Argon for ideale per la comprensione multimodale nativa di testo e immagini e l’analisi visiva dei documenti, sistemi rag aziendali e integrazioni api scalabili..
Domande Frequenti (FAQ)
Which is cheaper: Laguna XS 2.1 or Gemini 4 Argon?+
Laguna XS 2.1 costs $0.05/1M input and $0.2/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Laguna XS 2.1 or Gemini 4 Argon?+
Laguna XS 2.1 supports 262K tokens whereas Gemini 4 Argon supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Fonti ufficiali: Poolside & Google Official Documentation