Nemotron 3 Ultra 550B A55B vs GPT-6 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Nemotron 3 Ultra 550B A55B by NVIDIA against GPT-6 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.
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Live comparison: no in-depth editorial review has been published for this pair yet.
Nemotron 3 Ultra 550B A55B
Poids lourd open sourcede NVIDIA crowning ouvert-weight foundation géant intégrant 550B total paramètres, 1M fenêtre de contexte, et d'avant-garde d'entreprise raisonnement.
$1.00 / 1M
$3.00 / 1M
1M tokens
64.5%
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%
Différences Clés en un Coup d’Œil
- Nemotron 3 Ultra 550B A55B is 2.7x cheaper for API usage (input + output tokens combined).
- GPT-6 Sol is faster at 116 tok/s vs 65 tok/s.
- GPT-6 Sol leads on SWE-bench coding (82.1% vs 64.5%).
| Caractéristique | Nemotron 3 Ultra 550B A55B | GPT-6 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 60 | 93 |
Provider | NVIDIA | OpenAI |
Input Price Cost per million input tokens | $1.00 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $3.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.68 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 66K | 128K |
Throughput Speed Tokens generated per second | 65 tok/s | 116 tok/s |
SWE-bench Verified Real-world software engineering | 64.5% | 82.1% |
GPQA Diamond Graduate-level reasoning | 76% | 80.6% |
Cached Input Price Prompt caching discount per 1M tokens | $0.25 / 1M | $0.10 / 1M |
Qui gagne où ?
At-a-glance decision frameworkScores 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.
Nemotron 3 Ultra 550B A55B · Strengths & Key Advantages
- massif 550B capacité avec 55B actif inférence offrant de pointe raisonnement profondeur
- Colossal 1 millions token fenêtre de contexte avec flawless long-range recall
- à poids ouverts sous permissive license pour souverain national et d'entreprise déploiements
Considerations & Trade-offs
- nécessite substantiel DGX/H100 multinœud clusters pour auto-hébergement
- texte-seulement sans natif visuel traitement
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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Nemotron 3 Ultra 550B A55B | GPT-6 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.85 | $2.00 |
Output Tokens / Task Tokens generated per task | 48K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 24K | 36K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | Nemotron 3 Ultra 550B A55B | GPT-6 Sol |
|---|---|---|
| Official API Model ID (SDK) | nemotron-3-ultra-550b-a55b | gpt-6-sol |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-06 | 2026-09 |
| Knowledge Cutoff | February 2026 | April 2026 |
| Architecture | Colossal Sparse MoE (550B Total / 55B Active) | Cost-efficient frontier unified reasoning model |
| Parameters | 550B (55B active MoE) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($1/1M in) across full 1000K window | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.25/1M 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 | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | 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 | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 341 GB VRAM (4-bit Quantized) · 1183 GB VRAM (Native BF16) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | OpenAI Preparedness Framework Audited & System Card Published |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision |
| Output Modalities | text | text |
Nemotron 3 Ultra 550B A55B vs GPT-6 Sol: Réponses Rapides (FAQ)
Which is more intelligent, Nemotron 3 Ultra 550B A55B or GPT-6 Sol?
GPT-6 Sol is more intelligent. It scores 93 compared with 60 on the composite Intelligence Index.
Which model is faster?
GPT-6 Sol is faster, generating 116 tokens per second compared with 65 tokens per second.
Which model is cheaper to run?
Nemotron 3 Ultra 550B A55B is cheaper at $0.68 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Nemotron 3 Ultra 550B A55B has lower latency, with a time to first token of 0.62s compared with 1.16s.
Verdict
Choose Nemotron 3 Ultra 550B A55B for national ai initiatives, souverain defense intelligence, et d'entreprise-wide autonome agent swarms, or choose GPT-6 Sol for coût-sensitive de pointe travail et codage agentique.
Questions fréquentes
Which is cheaper: Nemotron 3 Ultra 550B A55B or GPT-6 Sol?+
Nemotron 3 Ultra 550B A55B costs $1/1M input and $3/1M output tokens, while GPT-6 Sol costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Nemotron 3 Ultra 550B A55B or GPT-6 Sol?+
Nemotron 3 Ultra 550B A55B supports 1M tokens whereas GPT-6 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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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: NVIDIA & OpenAI Official Documentation