Nex-N2-Mini vs GPT-6.1 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Nex-N2-Mini by Nex AGI against GPT-6.1 Sol by OpenAI 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.
Nex-N2-Mini
Motore di Ragionamento ProfondoNex-N2-Mini di Nex AGI è un modello di IA progettato per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, con finestra di contesto da 262K, velocità di 155 token/s, indice di intelligenza di 75/100 e tariffa
$0.08 / 1M
$0.32 / 1M
262.1K tokens
N/A
GPT-6.1 Sol
Modello Ammiraglia di FrontieraGPT-6.1 Sol di OpenAI è un modello di IA progettato per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, con finestra di contesto da 1M, velocità di 120 token/s, indice di intelligenza di 94/100
$2.00 / 1M
$10.00 / 1M
1M tokens
82.3%
Differenze Chiave a Colpo d’Occhio
- Nex-N2-Mini is 28.9x cheaper for API usage (input + output tokens combined).
- GPT-6.1 Sol has a larger context window (1M vs 262K tokens).
- Nex-N2-Mini is faster at 155 tok/s vs 120 tok/s.
| Feature | Nex-N2-Mini | GPT-6.1 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 75 | 94 |
Provider | Nex AGI | OpenAI |
Input Price Cost per million input tokens | $0.08 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $0.32 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.05 / 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 | 128K |
Throughput Speed Tokens generated per second | 155 tok/s | 120 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 82.3% |
GPQA Diamond Graduate-level reasoning | N/A | 80.8% |
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.
Nex-N2-Mini · Strengths & Key Advantages
- Finestra di contesto da 262K con capacità massima di output fino a 8K token (MMLU-Pro 72% · Arena Elo 1260)
- Throughput elevato di 155 token/secondo con latenza al primo token (TTFT) di soli 270 ms
- Economia API competitiva ($0.08/$0.32 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
GPT-6.1 Sol · Strengths & Key Advantages
- Finestra di contesto da 1M con capacità massima di output fino a 128K token (SWE-bench Verified 82.3% · GPQA Diamond 80.8%)
- Throughput elevato di 120 token/secondo con latenza al primo token (TTFT) di soli 1120 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 | Nex-N2-Mini | GPT-6.1 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.02 | $2.05 |
Output Tokens / Task Tokens generated per task | 12K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 1K | 36K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | Nex-N2-Mini | GPT-6.1 Sol |
|---|---|---|
| Official API Model ID (SDK) | nex-n2-mini | gpt-6-1-sol |
| API Protocol | Nex AGI REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-06 | 2026-09 |
| Knowledge Cutoff | March 2026 | April 2026 |
| Architecture | Compact Budget Reasoning Transformer | Near-Astra unified reasoning model |
| 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 ($0.08/1M in) across full 262K window | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.008/1M tokens | Automatic prefix caching at $0.1/1M (no extra cache-write fee) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| 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 | Nex AGI Production Safety & Alignment Verified | OpenAI Preparedness Framework Audited & System Card Published |
| 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 |
| Output Modalities | text | text |
Nex-N2-Mini vs GPT-6.1 Sol: Risposte Rapide (FAQ)
Which is more intelligent, Nex-N2-Mini or GPT-6.1 Sol?
GPT-6.1 Sol is more intelligent. It scores 94 compared with 75 on the composite Intelligence Index.
Which model is faster?
Nex-N2-Mini is faster, generating 155 tokens per second compared with 120 tokens per second.
Which model is cheaper to run?
Nex-N2-Mini is cheaper at $0.05 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Nex-N2-Mini has lower latency, with a time to first token of 0.27s compared with 1.12s.
Which model has a larger context window?
GPT-6.1 Sol has a larger context window, supporting 1M tokens compared with 262.1K tokens.
Verdetto
Choose Nex-N2-Mini for ideale per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, sistemi rag aziendali e integrazioni api scalabili., or choose GPT-6.1 Sol for ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi rag aziendali e integrazioni api scalabili..
Domande Frequenti (FAQ)
Which is cheaper: Nex-N2-Mini or GPT-6.1 Sol?+
Nex-N2-Mini costs $0.08/1M input and $0.32/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Nex-N2-Mini or GPT-6.1 Sol?+
Nex-N2-Mini supports 262K tokens whereas GPT-6.1 Sol 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: Nex AGI & OpenAI Official Documentation