Head-to-Head Model Comparison

Nemotron Cascade 2 30B A3B vs Mistral Small 4

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Nemotron Cascade 2 30B A3B vs Mistral Small 4: Benchmarks, Pricing & Speed Comparison

Nemotron Cascade 2 30B A3B von NVIDIA und Mistral Small 4 von Mistral AI gehören zu den führenden KI-Modellen. Nemotron Cascade 2 30B A3B bietet ein Kontextfenster von 256K Tokens bei API-Preisen von $0.10/$0.25 pro 1M Tokens, während Mistral Small 4 256K Tokens Kontext zu $0.10/$0.30 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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NVIDIA

Nemotron Cascade 2 30B A3B

Open-Weights-Reasoning-Modell

Nemotron Cascade 2 30B A3B von NVIDIA ist ein KI-Modell für Open-Weights-Reasoning mit transparenter Gedankenketten-Verarbeitung (Chain-of-Thought) mit 256K Kontextfenster, 155 Token/s Durchsatz, einem Intelligenz-Index von 46/100 und $0.1/

Intelligence Index46 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.25 / 1M

Context Window:

256K tokens

SWE-bench Verified:

39.5%

Mistral AI

Mistral Small 4

Ultraschnelle Echtzeit-Inferenz

Mistral Small 4 von Mistral AI ist ein KI-Modell für ultraschnelle Echtzeit-Antworten, niedrige Latenz und Hochdurchsatz-Routing mit 256K Kontextfenster, 120 Token/s Durchsatz, einem Intelligenz-Index von 48/100 und $0.1/$0.3 pro 1M Token.

Intelligence Index48 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.30 / 1M

Context Window:

256K tokens

SWE-bench Verified:

44.5%

Wichtigste Unterschiede auf einen Blick

  • Nemotron Cascade 2 30B A3B is 1.1x cheaper for API usage (input + output tokens combined).
  • Nemotron Cascade 2 30B A3B is faster at 155 tok/s vs 120 tok/s.
  • Mistral Small 4 leads on SWE-bench coding (44.5% vs 39.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron Cascade 2 30B A3BMistral Small 4
Intelligence Index
Composite reasoning & knowledge score (0-100)
4648
Provider
NVIDIAMistral AI
Input Price
Cost per million input tokens
$0.10 / 1M$0.10 / 1M
Output Price
Cost per million output tokens
$0.25 / 1M$0.30 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.06 / 1M$0.07 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text256K tokens~384 A4 pages of text
Max Output Tokens
Per single request
16K16K
Throughput Speed
Tokens generated per second
155 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
39.5%44.5%
GPQA Diamond
Graduate-level reasoning
55.2%56%
Cached Input Price
Prompt caching discount per 1M tokens
$0.02 / 1M$0.03 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding
Mistral Small 4
+5.0% SWE-bench lead
Cost
Nemotron Cascade 2 30B A3B
1.1x cheaper monthly runtime
Speed
Nemotron Cascade 2 30B A3B
+29% faster generation
Context
Tied
256K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

Nemotron Cascade 2 30B A3BMistral Small 4
SWE-bench Verified (Autonomous Coding)

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

39.5%vs44.5%
GPQA Diamond (Doctorate-Level Science & Math)

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

55.2%vs56%
MMLU-Pro (Multi-task Language Understanding)

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

76%vs78%
LMSYS Chatbot Arena Elo

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

1295ptsvs1315pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

35%vs38%
AIME (Advanced Math Competition)

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

65%vs66%
Long-Context Reasoning

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

77%vs80%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

155 tok/s vs120 tok/s

Latenz & Antwortzeit

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 Cascade 2 30B A3B0.27s
Mistral Small 40.34s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron Cascade 2 30B A3B3.50s
Mistral Small 44.51s

Interaktiver Token-Kosten-Simulator

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 Cascade 2 30B A3B Monthly API Bill
$0.41 / month
$0.1/1M in · $0.25/1M out
Mistral Small 4 Monthly API Bill
$0.47 / month
$0.1/1M in · $0.3/1M out
Nemotron Cascade 2 30B A3B saves approximately $0.06 / month (13%) under this workload.1.1x Savings

Nemotron Cascade 2 30B A3B · Strengths & Key Advantages

  • 256K Kontextfenster und bis zu 16K maximale Output-Token (SWE-bench Verified 39.5% · GPQA Diamond 55.2%)
  • Hohe Generierungsgeschwindigkeit von 155 Token/Sekunde bei nur 270 ms Erstlatenz (TTFT)
  • Offene Modellgewichte (30B (3B MoE)) für lokales Self-Hosting und Fine-Tuning über vLLM, SGLang oder Ollama
Considerations & Trade-offs
  • Erfordert dedizierte GPU-Hardware mit ausreichend VRAM für den lokalen Betrieb in voller Präzision
  • Bei extrem komplexen mehrstufigen Forschungsfragen bieten schwere Reasoning-Spezialmodelle noch tiefere Analysen

Mistral Small 4 · Strengths & Key Advantages

  • 256K Kontextfenster und bis zu 16K maximale Output-Token (SWE-bench Verified 44.5% · GPQA Diamond 56%)
  • Hohe Generierungsgeschwindigkeit von 120 Token/Sekunde bei nur 340 ms Erstlatenz (TTFT)
  • Offene Modellgewichte (24B) für lokales Self-Hosting und Fine-Tuning über vLLM, SGLang oder Ollama
Considerations & Trade-offs
  • Erfordert dedizierte GPU-Hardware mit ausreichend VRAM für den lokalen Betrieb in voller Präzision
  • Bei extrem komplexen mehrstufigen Forschungsfragen bieten schwere Reasoning-Spezialmodelle noch tiefere Analysen

Token Use & Task Economics

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

MetricNemotron Cascade 2 30B A3BMistral Small 4
Cost per Task
Estimated USD to finish one task
$0.11$0.12
Output Tokens / Task
Tokens generated per task
28K28K
Reasoning Tokens / Task
Thinking tokens burned per task
11K12K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron Cascade 2 30B A3BMistral Small 4
Official API Model ID (SDK)nemotron-cascade-2-30b-a3bmistral-small-4-latest
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-032026-03
Knowledge CutoffJanuary 2026January 2026
ArchitectureCascaded Speculative MoE (30B Total / 3B Active)Next-Gen Compact Multimodal Transformer
Parameters30B (3B active MoE)24B
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($0.1/1M in) across full 256K windowFlat rate ($0.1/1M in) across full 256K window
Prompt Cache Policy & TTLCached input at $0.02/1M tokensCached input at $0.03/1M tokens
Computer Use / GUI AgentAPI / 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 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 toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
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) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 15 GB VRAM (4-bit Quantized) · 52 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestexttext, vision
Output Modalitiestexttext

Nemotron Cascade 2 30B A3B vs Mistral Small 4: Schnelle Antworten (FAQ)

Which is more intelligent, Nemotron Cascade 2 30B A3B or Mistral Small 4?

Mistral Small 4 is more intelligent. It scores 48 compared with 46 on the composite Intelligence Index.

Which model is faster?

Nemotron Cascade 2 30B A3B is faster, generating 155 tokens per second compared with 120 tokens per second.

Which model is cheaper to run?

Nemotron Cascade 2 30B A3B is cheaper at $0.06 per 1M tokens blended, compared with $0.07 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nemotron Cascade 2 30B A3B has lower latency, with a time to first token of 0.27s compared with 0.34s.

Fazit

Sowohl Nemotron Cascade 2 30B A3B (Optimal für Open-Weights-Reasoning mit transparenter Gedankenketten-Verarbeitung (Chain-of-Thought), Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch Mistral Small 4 (Optimal für ultraschnelle Echtzeit-Antworten, niedrige Latenz und Hochdurchsatz-Routing, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Mistral Small 4 führt bei komplexem Reasoning und Coding, Nemotron Cascade 2 30B A3B liefert den höheren Token-Durchsatz und Nemotron Cascade 2 30B A3B ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Nemotron Cascade 2 30B A3B oder Mistral Small 4?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Mistral Small 4 vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Nemotron Cascade 2 30B A3B und Mistral Small 4?+

Nemotron Cascade 2 30B A3B kostet $0.10 / $0.25 pro 1M Input-/Output-Tokens, Mistral Small 4 liegt bei $0.10 / $0.30. Beim gewichteten Gesamtpreis ist Nemotron Cascade 2 30B A3B günstiger.

Welches Modell hat das größere Kontextfenster und die höhere Geschwindigkeit?+

Nemotron Cascade 2 30B A3B bietet 256K Tokens Kontext gegenüber 256K Tokens bei Mistral Small 4. Bei der Generierungsgeschwindigkeit liegt Nemotron Cascade 2 30B A3B vorn.

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.

Offizielle Quellen: Offizielle API-Dokumentation von NVIDIA und Mistral AI, Systemkarten und unabhängige Benchmark-Auswertungen (2026).