Head-to-Head Model Comparison

Nemotron Mini 4B Instruct vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

تمت المراجعة بواسطة فريق أبحاث GetInfoUsآخر مراجعة: October 2026السياسة التحريرية
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Compare Nemotron Mini 4B Instruct by NVIDIA against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.

مقارنة مباشرة (VS)

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NVIDIA

Nemotron Mini 4B Instruct

نموذج مفتوح الأوزان

نموذج Nemotron Mini 4B Instruct المقدم من NVIDIA يوفر نافذة سياق تصل إلى 128K رمز، بتكلفة $0.05 لكل مليون رمز إدخال و$0.15 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.

Intelligence Index35 / 100
Input Token:

$0.05 / 1M

Output Token:

$0.15 / 1M

Context Window:

128K tokens

SWE-bench Verified:

22%

OpenAI

GPT-6 Astra

نموذج استدلال عميق

نموذج GPT-6 Astra المقدم من OpenAI يوفر نافذة سياق تصل إلى 1M رمز، بتكلفة $10.0 لكل مليون رمز إدخال و$50.0 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

أهم الفروقات في لمحة

  • Nemotron Mini 4B Instruct is 256.3x cheaper for API usage (input + output tokens combined).
  • GPT-6 Astra has a larger context window (272K vs 128K tokens).
  • Nemotron Mini 4B Instruct is faster at 160 tok/s vs 100 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 22.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron Mini 4B InstructGPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
3596
Provider
NVIDIAOpenAI
Input Price
Cost per million input tokens
$0.05 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$0.15 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.04 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
4K128K
Throughput Speed
Tokens generated per second
160 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
22%82.4%
GPQA Diamond
Graduate-level reasoning
38%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$0.02 / 1M$1.00 / 1M

من يتفوق في كل مجال؟

At-a-glance decision framework
Coding
GPT-6 Astra
+60.4% SWE-bench lead
Cost
Nemotron Mini 4B Instruct
256.3x cheaper monthly runtime
Speed
Nemotron Mini 4B Instruct
+60% faster generation
Context
GPT-6 Astra
272K tokens window

نتائج الاختبارات المعيارية الموثقة

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

Nemotron Mini 4B InstructGPT-6 Astra
SWE-bench Verified (Autonomous Coding)

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

22%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

38%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

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

58.5%vs89.9%
LMSYS Chatbot Arena Elo

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

1180ptsvs1520pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs18.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

20%vs63.8%
SciCode (Scientific Computing)

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

N/Avs54.9%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.8%
AIME (Advanced Math Competition)

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

38%vs93.6%
Long-Context Reasoning

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

58%vs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

160 tok/s vs100 tok/s

زمن الاستجابة والسرعة

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 Mini 4B Instruct0.25s
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron Mini 4B Instruct3.38s
GPT-6 Astra5.95s

محاكي تكلفة الرموز التفاعلي

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 Mini 4B Instruct Monthly API Bill
$0.24 / month
$0.05/1M in · $0.15/1M out
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
Nemotron Mini 4B Instruct saves approximately $61.26 / month (100%) under this workload.256.3x Savings

Nemotron Mini 4B Instruct · Strengths & Key Advantages

  • بنية Pruned and Distilled Compact Transformer متطورة من NVIDIA مع سعة سياق تبلغ 128K رمز
  • كفاءة عالية في التكلفة ($0.05/1M إدخال و$0.15/1M إخراج) وسرعة استجابة ممتازة
  • أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
  • يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
  • قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة

GPT-6 Astra · Strengths & Key Advantages

  • بنية Omni-Adaptive Autoregressive with Dynamic CoT متطورة من OpenAI مع سعة سياق تبلغ 1M رمز
  • كفاءة عالية في التكلفة ($10.0/1M إدخال و$50.0/1M إخراج) وسرعة استجابة ممتازة
  • أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
  • يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
  • قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة

Token Use & Task Economics

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

MetricNemotron Mini 4B InstructGPT-6 Astra
Cost per Task
Estimated USD to finish one task
$0.03$2.15
Output Tokens / Task
Tokens generated per task
15K58K
Reasoning Tokens / Task
Thinking tokens burned per task
0K32K

المواصفات التقنية

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron Mini 4B InstructGPT-6 Astra
Official API Model ID (SDK)nemotron-mini-4bgpt-6-astra
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI Responses API & Chat Completions v1
Release Date2024-082026-09
Knowledge CutoffJune 2024June 2026
ArchitecturePruned and Distilled Compact TransformerOmni-Adaptive Autoregressive with Dynamic CoT
Parameters4BConfidential
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) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.05/1M in) across full 128K windowFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTLCached input at $0.02/1M tokensAutomatic prefix caching at $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)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 9 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 Modalitiestexttext, vision, audio
Output Modalitiestexttext, audio

Nemotron Mini 4B Instruct vs GPT-6 Astra: إجابات سريعة (FAQ)

Which is more intelligent, Nemotron Mini 4B Instruct or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 35 on the composite Intelligence Index.

Which model is faster?

Nemotron Mini 4B Instruct is faster, generating 160 tokens per second compared with 100 tokens per second.

Which model is cheaper to run?

Nemotron Mini 4B Instruct is cheaper at $0.04 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nemotron Mini 4B Instruct has lower latency, with a time to first token of 0.25s compared with 0.95s.

Which model has a larger context window?

GPT-6 Astra has a larger context window, supporting 272K tokens compared with 128K tokens.

الحكم النهائي

Choose Nemotron Mini 4B Instruct for أتمتة الأعمال، تطوير البرمجيات، الوكلاء الأذكياء (ai agents)، وتطبيقات nvidia الإنتاجية, or choose GPT-6 Astra for أتمتة الأعمال، تطوير البرمجيات، الوكلاء الأذكياء (ai agents)، وتطبيقات openai الإنتاجية.

الأسئلة الشائعة (FAQ)

Which is cheaper: Nemotron Mini 4B Instruct or GPT-6 Astra?+

Nemotron Mini 4B Instruct costs $0.05/1M input and $0.15/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.

Which model has a larger context window: Nemotron Mini 4B Instruct or GPT-6 Astra?+

Nemotron Mini 4B Instruct supports 128K tokens whereas GPT-6 Astra supports 272K 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.

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.

المصادر الرسمية: NVIDIA & OpenAI Official Documentation