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Nemotron 3 Nano Omni 30B A3B Reasoning vs GPT-6.1 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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Compare Nemotron 3 Nano Omni 30B A3B Reasoning by NVIDIA against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

आमने-सामने मॉडल तुलना (VS)

किसी भी मॉडल को बदलें और तुलना करें

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Live comparison: no in-depth editorial review has been published for this pair yet.

Popular Matchups:
NVIDIA

Nemotron 3 Nano Omni 30B A3B Reasoning

ओपन-वेट्स मॉडल

NVIDIA द्वारा विकसित Nemotron 3 Nano Omni 30B A3B Reasoning एक उन्नत AI मॉडल है, जिसमें 256K टोकन का कॉन्टेक्स्ट विंडो और $0.2/1M इनपुट तथा $0.6/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।

Intelligence Index48 / 100
Input Token:

$0.20 / 1M

Output Token:

$0.60 / 1M

Context Window:

256K tokens

SWE-bench Verified:

42%

OpenAI

GPT-6.1 Sol

डीप रीजनिंग मॉडल

OpenAI द्वारा विकसित GPT-6.1 Sol एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $2.0/1M इनपुट तथा $10.0/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।

Intelligence Index94 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

एक नज़र में मुख्य अंतर

  • Nemotron 3 Nano Omni 30B A3B Reasoning is 13.3x cheaper for API usage (input + output tokens combined).
  • GPT-6.1 Sol has a larger context window (1M vs 256K tokens).
  • GPT-6.1 Sol is faster at 120 tok/s vs 105 tok/s.
  • GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 42.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron 3 Nano Omni 30B A3B ReasoningGPT-6.1 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
4894
Provider
NVIDIAOpenAI
Input Price
Cost per million input tokens
$0.20 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$0.60 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.14 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
16K128K
Throughput Speed
Tokens generated per second
105 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
42%82.3%
GPQA Diamond
Graduate-level reasoning
56.5%80.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.05 / 1M$0.10 / 1M

किस क्षेत्र में कौन आगे है?

At-a-glance decision framework
Coding
GPT-6.1 Sol
+40.3% SWE-bench lead
Cost
Nemotron 3 Nano Omni 30B A3B Reasoning
13.3x cheaper monthly runtime
Speed
GPT-6.1 Sol
+14% faster generation
Context
GPT-6.1 Sol
1M tokens window

सत्यापित बेंचमार्क स्कोर तुलना

Official evaluation metrics verified by independent third-party research labs.

Nemotron 3 Nano Omni 30B A3B ReasoningGPT-6.1 Sol
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

42%vs82.3%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

56.5%vs80.8%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

77.2%vs89.9%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1310ptsvs1519pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs18.1%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

36.5%vs63.6%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs54.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.7%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

66%vs93.5%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

78%vs91%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs120 tok/s

लेटेंसी और रिस्पॉन्स समय

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Nemotron 3 Nano Omni 30B A3B Reasoning0.38s
GPT-6.1 Sol1.12s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron 3 Nano Omni 30B A3B Reasoning5.14s
GPT-6.1 Sol5.29s

रियल-टाइम टोकन लागत सिम्युलेटर

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Nemotron 3 Nano Omni 30B A3B Reasoning Monthly API Bill
$0.92 / month
$0.2/1M in · $0.6/1M out
GPT-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Nemotron 3 Nano Omni 30B A3B Reasoning saves approximately $11.23 / month (92%) under this workload.13.3x Savings

Nemotron 3 Nano Omni 30B A3B Reasoning · Strengths & Key Advantages

  • NVIDIA की उन्नत Omnimodal Sparse MoE (30B Total / 3B Active) आर्किटेक्चर और 256K कॉन्टेक्स्ट विंडो क्षमता
  • किफायती और पारदर्शी API मूल्य ($0.2/1M इनपुट, $0.6/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
  • जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
  • बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
  • विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है

GPT-6.1 Sol · Strengths & Key Advantages

  • OpenAI की उन्नत Near-Astra unified reasoning model आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
  • किफायती और पारदर्शी API मूल्य ($2.0/1M इनपुट, $10.0/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
  • जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
  • बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
  • विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricNemotron 3 Nano Omni 30B A3B ReasoningGPT-6.1 Sol
Cost per Task
Estimated USD to finish one task
$0.22$2.05
Output Tokens / Task
Tokens generated per task
28K62K
Reasoning Tokens / Task
Thinking tokens burned per task
12K36K

तकनीकी विशिष्टताएँ (Specs)

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron 3 Nano Omni 30B A3B ReasoningGPT-6.1 Sol
Official API Model ID (SDK)nemotron-3-nano-omni-30b-a3bgpt-6-1-sol
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI Responses API & Chat Completions v1
Release Date2026-042026-09
Knowledge CutoffFebruary 2026April 2026
ArchitectureOmnimodal Sparse MoE (30B Total / 3B Active)Near-Astra unified reasoning model
Parameters30B (3B 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 Cloud10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.2/1M in) across full 256K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.05/1M tokensAutomatic prefix caching at $0.1/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpen-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 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, vision, audiotext, vision
Output Modalitiestexttext

Nemotron 3 Nano Omni 30B A3B Reasoning vs GPT-6.1 Sol: त्वरित प्रश्नोत्तर (FAQ)

Which is more intelligent, Nemotron 3 Nano Omni 30B A3B Reasoning or GPT-6.1 Sol?

GPT-6.1 Sol is more intelligent. It scores 94 compared with 48 on the composite Intelligence Index.

Which model is faster?

GPT-6.1 Sol is faster, generating 120 tokens per second compared with 105 tokens per second.

Which model is cheaper to run?

Nemotron 3 Nano Omni 30B A3B Reasoning is cheaper at $0.14 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nemotron 3 Nano Omni 30B A3B Reasoning has lower latency, with a time to first token of 0.38s 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 256K tokens.

निष्कर्ष

Choose Nemotron 3 Nano Omni 30B A3B Reasoning for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और nvidia आधारित प्रोडक्शन सिस्टम, or choose GPT-6.1 Sol for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और openai आधारित प्रोडक्शन सिस्टम.

अक्सर पूछे जाने वाले प्रश्न (FAQ)

Which is cheaper: Nemotron 3 Nano Omni 30B A3B Reasoning or GPT-6.1 Sol?+

Nemotron 3 Nano Omni 30B A3B Reasoning costs $0.2/1M input and $0.6/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Nemotron 3 Nano Omni 30B A3B Reasoning or GPT-6.1 Sol?+

Nemotron 3 Nano Omni 30B A3B Reasoning supports 256K tokens whereas GPT-6.1 Sol supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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.

स्रोत: NVIDIA & OpenAI Official Documentation