Head-to-Head Model Comparison

Nemotron Mini 4B Instruct vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Vérifié par l’équipe de recherche de GetInfoUsDernière révision : October 2026Politique éditoriale
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NVIDIAAnthropicopen-sourceflagship

Compare Nemotron Mini 4B Instruct by NVIDIA against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Comparaison Face-à-Face (VS)

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Popular Matchups:
NVIDIA

Nemotron Mini 4B Instruct

Nemotron minuscule

ultra-compact 4B instruct modèle optimized par NVIDIA pour sur-device roleplay, RAG assistance, et PC périphérie déploiements.

Intelligence Index35 / 100
Input Token:

$0.05 / 1M

Output Token:

$0.15 / 1M

Context Window:

128K tokens

SWE-bench Verified:

22%

Anthropic

Claude Opus 5.5

Titan d'intelligence de pointe

d'Anthropic pinnacle modèle de pointe conçu pour à long terme agentic ingénierie logicielle, dense multimodal document synthèse, et autonome recherche flux de travail.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Différences Clés en un Coup d’Œil

  • Nemotron Mini 4B Instruct is 102.5x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 128K tokens).
  • Nemotron Mini 4B Instruct is faster at 160 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 22.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaractéristiqueNemotron Mini 4B InstructClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
3594
Provider
NVIDIAAnthropic
Input Price
Cost per million input tokens
$0.05 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$0.15 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.04 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
4K128K
Throughput Speed
Tokens generated per second
160 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
22%84.6%
GPQA Diamond
Graduate-level reasoning
38%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.02 / 1M$0.40 / 1M

Qui gagne où ?

At-a-glance decision framework
Code
Claude Opus 5.5
+62.6% SWE-bench lead
Coût
Nemotron Mini 4B Instruct
102.5x cheaper monthly runtime
Vitesse
Nemotron Mini 4B Instruct
+105% faster generation
Contexte
Claude Opus 5.5
1M tokens window

Scores de Benchmarks Vérifiés

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

Nemotron Mini 4B InstructClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

22%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

38%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

58.5%vs91.5%
LMSYS Chatbot Arena Elo

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

1180ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

20%vs66.4%
SciCode (Scientific Computing)

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

N/Avs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs83.1%
AIME (Advanced Math Competition)

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

38%vs95.4%
Long-Context Reasoning

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

58%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

160 tok/s vs78 tok/s

Latence et Temps de Réponse

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
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron Mini 4B Instruct3.38s
Claude Opus 5.57.81s

Simulateur Interactif de Coût de Tokens

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
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Nemotron Mini 4B Instruct saves approximately $24.36 / month (99%) under this workload.102.5x Savings

Nemotron Mini 4B Instruct · Strengths & Key Advantages

  • ultra-léger 4B empreinte running smoothly sur grand public RTX GPUs et laptops
  • Engineered par NVIDIA avec TensorRT-LLM acceleration pour extreme débit
  • complet 128K fenêtre de contexte avec permissive à poids ouverts
Considerations & Trade-offs
  • limité raisonnement profondeur sur complexe mathématique et scientifique tâches
  • texte-seulement sans natif multimodal traitement

Claude Opus 5.5 · Strengths & Key Advantages

  • inégalé autonome multi-étapes codage agentique et refactorisation
  • Flawless multidocument raisonnement sur 1M token contexte avec no long-prompt surcharge
  • le plus élevé Artificial analyse intelligence Index ever measured (58/100), leading SWE-bench Pro à 89.9%
  • Precise outil exécution avec robust error-recovery boucles
Considerations & Trade-offs
  • Premium sortie tarification ($20.00/M) plus heavy raisonnement-token usage (~119K sortie tokens par index tâche) keeps long agentic fonctionne expensive
  • long pensée times à maximum effort peut push un unique hard agentic tâche toward ~$13

Token Use & Task Economics

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

MetricNemotron Mini 4B InstructClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.03$3.85
Output Tokens / Task
Tokens generated per task
15K68K
Reasoning Tokens / Task
Thinking tokens burned per task
0K42K

Spécifications Techniques

Architecture, release timeline, capabilities, and modalities.

CaractéristiqueNemotron Mini 4B InstructClaude Opus 5.5
Official API Model ID (SDK)nemotron-mini-4bclaude-opus-5-5-20260901
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2024-082026-09
Knowledge CutoffJune 2024June 2026
ArchitecturePruned and Distilled Compact TransformerExtended Autonomous Hybrid Reasoning Transformer
Parameters4BConfidential
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.05/1M in) across full 128K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.02/1M tokens$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
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 Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token)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) · 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)Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
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
Output Modalitiestexttext

Nemotron Mini 4B Instruct vs Claude Opus 5.5: Réponses Rapides (FAQ)

Which is more intelligent, Nemotron Mini 4B Instruct or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 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 78 tokens per second.

Which model is cheaper to run?

Nemotron Mini 4B Instruct is cheaper at $0.04 per 1M tokens blended, compared with $3.08 (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 1.40s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 128K tokens.

Verdict

Choose Nemotron Mini 4B Instruct for local desktop ai companions, offline périphérie pcs, et élevé-vitesse données extraction, or choose Claude Opus 5.5 for grand-échelle logiciel development agents, d'entreprise codebases, et mission critique scientifique synthèse.

Questions fréquentes

Which is cheaper: Nemotron Mini 4B Instruct or Claude Opus 5.5?+

Nemotron Mini 4B Instruct costs $0.05/1M input and $0.15/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Nemotron Mini 4B Instruct or Claude Opus 5.5?+

Nemotron Mini 4B Instruct supports 128K tokens whereas Claude Opus 5.5 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.

Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: NVIDIA & Anthropic Official Documentation