GPT-6.1 Sol vs Aion-Mini
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare GPT-6.1 Sol by OpenAI against Aion-Mini by AionLabs across real-world coding, reasoning, token economics, and latency.
원하는 AI 모델 선택 및 실시간 비교
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Live comparison: no in-depth editorial review has been published for this pair yet.
GPT-6.1 Sol
심층 추론 모델OpenAI의 GPT-6.1 Sol 모델은 1M 토큰 컨텍스트 윈도우와 입력 $2.0/1M 토큰, 출력 $10.0/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$2.00 / 1M
$10.00 / 1M
1M tokens
82.3%
Aion-Mini
심층 추론 모델AionLabs의 Aion-Mini 모델은 131K 토큰 컨텍스트 윈도우와 입력 $0.08/1M 토큰, 출력 $0.32/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$0.08 / 1M
$0.32 / 1M
131.1K tokens
N/A
한눈에 보는 핵심 차이점
- Aion-Mini is 28.9x cheaper for API usage (input + output tokens combined).
- GPT-6.1 Sol has a larger context window (1M vs 131K tokens).
- Aion-Mini is faster at 150 tok/s vs 120 tok/s.
| Feature | GPT-6.1 Sol | Aion-Mini |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 94 | 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 | 120 tok/s | 150 tok/s |
SWE-bench Verified Real-world software engineering | 82.3% | N/A |
GPQA Diamond Graduate-level reasoning | 80.8% | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.10 / 1M | $0.01 / 1M |
부문별 우위 모델
At-a-glance decision frameworkEvaluations ongoing
검증된 벤치마크 점수 비교
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.
지연 시간(Latency) 및 응답 속도
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
실시간 API 토큰 비용 시뮬레이터
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GPT-6.1 Sol · Strengths & Key Advantages
- OpenAI의 첨단 Near-Astra unified reasoning model 아키텍처와 최대 1M 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $2.0/1M, 출력 $10.0/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Aion-Mini · Strengths & Key Advantages
- AionLabs의 첨단 Compact Scientific Routing Transformer 아키텍처와 최대 131K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $0.08/1M, 출력 $0.32/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT-6.1 Sol | Aion-Mini |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.05 | $0.03 |
Output Tokens / Task Tokens generated per task | 62K | 10K |
Reasoning Tokens / Task Thinking tokens burned per task | 36K | 1K |
기술 사양 (Specifications)
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT-6.1 Sol | Aion-Mini |
|---|---|---|
| Official API Model ID (SDK) | gpt-6-1-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 | Near-Astra 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-6.1 Sol vs Aion-Mini: 핵심 요약 문답 (FAQ)
Which is more intelligent, GPT-6.1 Sol or Aion-Mini?
GPT-6.1 Sol is more intelligent. It scores 94 compared with 74 on the composite Intelligence Index.
Which model is faster?
Aion-Mini is faster, generating 150 tokens per second compared with 120 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 1.12s.
Which model has a larger context window?
GPT-6.1 Sol has a larger context window, supporting 1M tokens compared with 131.1K tokens.
종합 평가
Choose GPT-6.1 Sol for 기업 업무 자동화, 소프트웨어 개발, 자율형 ai 에이전트 및 openai 기반 프로덕션 파이프라인, or choose Aion-Mini for 기업 업무 자동화, 소프트웨어 개발, 자율형 ai 에이전트 및 aionlabs 기반 프로덕션 파이프라인.
자주 묻는 질문 (FAQ)
Which is cheaper: GPT-6.1 Sol or Aion-Mini?+
GPT-6.1 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-6.1 Sol or Aion-Mini?+
GPT-6.1 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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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.
공식 출처: OpenAI & AionLabs Official Documentation