GPT-6 Sol vs Aion-Mini
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare GPT-6 Sol by OpenAI against Aion-Mini by AionLabs across real-world coding, reasoning, token economics, and latency.
Changez et Comparez les Modèles
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Live comparison: no in-depth editorial review has been published for this pair yet.
GPT-6 Sol
GPT-6 économiqueun GPT-6 palier offrant complexe codage et professionnel travail à half le prix de GPT-5.6 Sol.
$2.00 / 1M
$10.00 / 1M
1M tokens
82.1%
Aion-Mini
Duo de raisonnementcompact modèle de raisonnement développé pour rapide scientifique données triage, laboratoire metadata balisage, et quick entité extraction.
$0.08 / 1M
$0.32 / 1M
131.1K tokens
N/A
Différences Clés en un Coup d’Œil
- Aion-Mini is 28.9x cheaper for API usage (input + output tokens combined).
- GPT-6 Sol has a larger context window (1M vs 131K tokens).
- Aion-Mini is faster at 150 tok/s vs 116 tok/s.
| Caractéristique | GPT-6 Sol | Aion-Mini |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 93 | 74 |
Provider | OpenAI | AionLabs |
Input Price Cost per million input tokens | $2.00 / 1M | $0.08 / 1M |
Output Price Cost per million output tokens | $10.00 / 1M | $0.32 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.47 / 1M | $0.05 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 131.1K tokens~197 A4 pages of text |
Max Output Tokens Per single request | 128K | 8K |
Throughput Speed Tokens generated per second | 116 tok/s | 150 tok/s |
SWE-bench Verified Real-world software engineering | 82.1% | N/A |
GPQA Diamond Graduate-level reasoning | 80.6% | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.10 / 1M | $0.01 / 1M |
Qui gagne où ?
At-a-glance decision frameworkEvaluations ongoing
Scores de Benchmarks Vérifiés
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.
Latence et Temps de Réponse
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulateur Interactif de Coût de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GPT-6 Sol · Strengths & Key Advantages
- Roughly 50% cheaper que GPT-5.6 Sol
- Error rate close à half du previous génération
- solide codage agentique et professionnel flux de travail
- Roughly half le prix de GPT-5.6 Sol avec meilleur error rates
Considerations & Trade-offs
- Weaker que GPT-6 Astra sur le hardest tâches
- Sits close dans prix à GPT-6.1 Sol, which est stronger
Aion-Mini · Strengths & Key Advantages
- rapide 150 tokens/sec débit avec faible initial latence
- abordable $0.08 / 1M entrée tokens prix structure
- spécialisé scientifique tokenization minimizing word fragmentation
Considerations & Trade-offs
- inférieur capacité sur profond multi-page mathématique dérivations
- pas suited pour à long terme autonome agents
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT-6 Sol | Aion-Mini |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.00 | $0.03 |
Output Tokens / Task Tokens generated per task | 62K | 10K |
Reasoning Tokens / Task Thinking tokens burned per task | 36K | 1K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | GPT-6 Sol | Aion-Mini |
|---|---|---|
| Official API Model ID (SDK) | gpt-6-sol | aion-mini |
| API Protocol | OpenAI Responses API & Chat Completions v1 | AionLabs REST API (OpenAI-Compatible) |
| Release Date | 2026-09 | 2026-07 |
| Knowledge Cutoff | April 2026 | May 2026 |
| Architecture | Cost-efficient frontier unified reasoning model | Compact Scientific Routing Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($2/1M in) across full 1000K window | Flat rate ($0.08/1M in) across full 131K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.1/1M (no extra cache-write fee) | Cached input at $0.008/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) |
| 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 | OpenAI Preparedness Framework Audited & System Card Published | AionLabs Production Safety & Alignment 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, vision | text |
| Output Modalities | text | text |
GPT-6 Sol vs Aion-Mini: Réponses Rapides (FAQ)
Which is more intelligent, GPT-6 Sol or Aion-Mini?
GPT-6 Sol is more intelligent. It scores 93 compared with 74 on the composite Intelligence Index.
Which model is faster?
Aion-Mini is faster, generating 150 tokens per second compared with 116 tokens per second.
Which model is cheaper to run?
Aion-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?
Aion-Mini has lower latency, with a time to first token of 0.28s compared with 1.16s.
Which model has a larger context window?
GPT-6 Sol has a larger context window, supporting 1M tokens compared with 131.1K tokens.
Verdict
Choose GPT-6 Sol for coût-sensitive de pointe travail et codage agentique, or choose Aion-Mini for scientifique article de recherche metadata extraction, lab échantillon balisage, et rapide médical triage.
Questions fréquentes
Which is cheaper: GPT-6 Sol or Aion-Mini?+
GPT-6 Sol costs $2/1M input and $10/1M output tokens, while Aion-Mini costs $0.08/1M input and $0.32/1M output tokens.
Which model has a larger context window: GPT-6 Sol or Aion-Mini?+
GPT-6 Sol supports 1M tokens whereas Aion-Mini supports 131K tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: OpenAI & AionLabs Official Documentation