Aion-3.0 vs Aion-Mini
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Aion-3.0 by AionLabs and Aion-Mini by AionLabs represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Aion-Mini holds a notable pricing advantage for token ingestion. On output generation, Aion-Mini is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 131K tokens. In latency-sensitive production environments, Aion-Mini leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
Changez et Comparez les Modèles
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Aion-3.0
Duo de raisonnementde pointe scientifique modèle de raisonnement conçu pour biochimique recherche, formel mathématique logique, et multi-étapes theorem proving.
$0.50 / 1M
$2.00 / 1M
131.1K tokens
N/A
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 6.2x cheaper for API usage (input + output tokens combined).
- Aion-Mini is faster at 150 tok/s vs 80 tok/s.
| Caractéristique | Aion-3.0 | Aion-Mini |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 83 | 74 |
Provider | AionLabs | AionLabs |
Input Price Cost per million input tokens | $0.50 / 1M | $0.08 / 1M |
Output Price Cost per million output tokens | $2.00 / 1M | $0.32 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.34 / 1M | $0.05 / 1M |
Context Window Maximum input + output tokens | 131.1K tokens~197 A4 pages of text | 131.1K tokens~197 A4 pages of text |
Max Output Tokens Per single request | 16K | 8K |
Throughput Speed Tokens generated per second | 80 tok/s | 150 tok/s |
SWE-bench Verified Real-world software engineering | N/A | N/A |
GPQA Diamond Graduate-level reasoning | 63.5% | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.05 / 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.
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.
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.
Aion-3.0 · Strengths & Key Advantages
- solide proficiency dans scientifique littérature scientifique, biomédical terminology, et formel logique
- Robust multi-étapes deductive raisonnement capacités
- Clean structuré JSON outputs pour laboratoire pipeline intégration
Considerations & Trade-offs
- Relatively compact 131K fenêtre de contexte par rapport à millions-token peers
- supérieur latence sur heavy raisonnement requests
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 | Aion-3.0 | Aion-Mini |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.16 | $0.03 |
Output Tokens / Task Tokens generated per task | 20K | 10K |
Reasoning Tokens / Task Thinking tokens burned per task | 7K | 1K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | Aion-3.0 | Aion-Mini |
|---|---|---|
| Official API Model ID (SDK) | aion-3-0 | aion-mini |
| API Protocol | AionLabs REST API (OpenAI-Compatible) | AionLabs REST API (OpenAI-Compatible) |
| Release Date | 2026-07 | 2026-07 |
| Knowledge Cutoff | May 2026 | May 2026 |
| Architecture | Deliberate Scientific Reasoning Transformer | Compact Scientific Routing Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.5/1M in) across full 131K window | Flat rate ($0.08/1M in) across full 131K window |
| Prompt Cache Policy & TTL | Cached input at $0.05/1M tokens | Cached input at $0.008/1M tokens |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | 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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) | 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 | AionLabs Production Safety & Alignment Verified | 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 | text |
| Output Modalities | text | text |
Aion-3.0 vs Aion-Mini: Réponses Rapides (FAQ)
Which is more intelligent, Aion-3.0 or Aion-Mini?
Aion-3.0 is more intelligent. It scores 83 compared with 74 on the composite Intelligence Index.
Which model is faster?
Aion-Mini is faster, generating 150 tokens per second compared with 80 tokens per second.
Which model is cheaper to run?
Aion-Mini is cheaper at $0.05 per 1M tokens blended, compared with $0.34 (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 0.52s.
Verdict
Verdict & Model Selection Recommendation: Choose Aion-3.0 if your priority is Biotech research, chemical synthesis workflows, and formal logical analysis. Its performance in demanding tasks justifies its operational token cost. Choose Aion-Mini if your workflow prioritizes Scientific paper metadata extraction, lab sample tagging, and rapid medical triage. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Questions fréquentes
How does Aion-3.0 compare to Aion-Mini in API token pricing and cost per token?+
Aion-3.0 costs $0.50 per 1M input tokens and $2.00 per 1M output tokens, whereas Aion-Mini costs $0.08 input and $0.32 output. Overall, Aion-Mini is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Aion-3.0 or Aion-Mini?+
Both Aion-3.0 and Aion-Mini offer an identical context window of 131K tokens (~98k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: Aion-3.0 or Aion-Mini?+
Aion-3.0 scores at the frontier of coding benchmarks, while Aion-Mini scores competitively for software generation. For complex autonomous debugging and agentic engineering, Aion-3.0 provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between Aion-3.0 and Aion-Mini?+
Aion-3.0 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Aion-Mini provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Aion-3.0 and Aion-Mini?+
Aion-3.0 generates approximately 80 tokens per second, while Aion-Mini delivers 150 tokens per second. In latency-sensitive production environments, Aion-Mini provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Aion-3.0 and Aion-Mini to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Aion-Mini to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Aion-3.0. This tiered routing pattern cuts overall API bills by up to 70%.
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: GetInfoUs Independent AI Benchmarks & Official API Specs