Head-to-Head Model Comparison

Mistral Small 4 vs Claude Haiku 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs 연구팀 검토 완료최종 검토일: October 2026편집 정책
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Mistral Small 4 vs Claude Haiku 5.5: Benchmarks, Pricing & Speed Comparison

Mistral Small 4 by Mistral AI and Claude Haiku 5.5 by Anthropic represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Mistral Small 4 holds a notable pricing advantage for token ingestion. On output generation, Mistral Small 4 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Mistral Small 4 provides an expanded memory horizon with 256K tokens. In latency-sensitive production environments, Claude Haiku 5.5 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.

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Mistral AI

Mistral Small 4

오픈 웨이트 모델

Mistral AI의 Mistral Small 4 모델은 256K 토큰 컨텍스트 윈도우와 입력 $0.15/1M 토큰, 출력 $0.6/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.

Intelligence Index48 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.30 / 1M

Context Window:

256K tokens

SWE-bench Verified:

44.5%

Anthropic

Claude Haiku 5.5

심층 추론 모델

Anthropic의 Claude Haiku 5.5 모델은 200K 토큰 컨텍스트 윈도우와 입력 $1/1M 토큰, 출력 $5/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.

Intelligence Index62 / 100
Input Token:

$1.00 / 1M

Output Token:

$5.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

68.4%

한눈에 보는 핵심 차이점

  • Mistral Small 4 is 13.2x cheaper for API usage (input + output tokens combined).
  • Mistral Small 4 has a larger context window (256K vs 200K tokens).
  • Claude Haiku 5.5 is faster at 160 tok/s vs 120 tok/s.
  • Claude Haiku 5.5 leads on SWE-bench coding (68.4% vs 44.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureMistral Small 4Claude Haiku 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
4862
Provider
Mistral AIAnthropic
Input Price
Cost per million input tokens
$0.10 / 1M$1.00 / 1M
Output Price
Cost per million output tokens
$0.30 / 1M$5.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.07 / 1M$0.77 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
16K64K
Throughput Speed
Tokens generated per second
120 tok/s160 tok/s
SWE-bench Verified
Real-world software engineering
44.5%68.4%
GPQA Diamond
Graduate-level reasoning
56%69.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.03 / 1M$0.10 / 1M

부문별 우위 모델

At-a-glance decision framework
Coding
Claude Haiku 5.5
+23.9% SWE-bench lead
Cost
Mistral Small 4
13.2x cheaper monthly runtime
Speed
Claude Haiku 5.5
+33% faster generation
Context
Mistral Small 4
256K tokens window

검증된 벤치마크 점수 비교

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

Mistral Small 4Claude Haiku 5.5
SWE-bench Verified (Autonomous Coding)

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

44.5%vs68.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

56%vs69.8%
MMLU-Pro (Multi-task Language Understanding)

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

78%vs83.2%
LMSYS Chatbot Arena Elo

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

1315ptsvs1370pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

38%vsN/A
AIME (Advanced Math Competition)

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

66%vsN/A
Long-Context Reasoning

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

80%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

120 tok/s vs160 tok/s

지연 시간(Latency) 및 응답 속도

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
Mistral Small 40.34s
Claude Haiku 5.50.22s
Est. End-to-End Response (500 tokens)TTFT + generation time
Mistral Small 44.51s
Claude Haiku 5.53.35s

실시간 API 토큰 비용 시뮬레이터

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)
Mistral Small 4 Monthly API Bill
$0.47 / month
$0.1/1M in · $0.3/1M out
Claude Haiku 5.5 Monthly API Bill
$6.15 / month
$1/1M in · $5/1M out
Mistral Small 4 saves approximately $5.69 / month (92%) under this workload.13.2x Savings

Mistral Small 4 · Strengths & Key Advantages

  • Mistral AI의 첨단 Next-Gen Compact Multimodal Transformer 아키텍처와 최대 256K 토큰 컨텍스트 지원
  • 경쟁력 있는 API 가격(입력 $0.15/1M, 출력 $0.6/1M)과 빠른 응답 속도
  • 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
  • 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
  • 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨

Claude Haiku 5.5 · Strengths & Key Advantages

  • Anthropic의 첨단 Ultra-Fast Lightweight Reasoning Transformer 아키텍처와 최대 200K 토큰 컨텍스트 지원
  • 경쟁력 있는 API 가격(입력 $1/1M, 출력 $5/1M)과 빠른 응답 속도
  • 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
  • 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
  • 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨

Token Use & Task Economics

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

MetricMistral Small 4Claude Haiku 5.5
Cost per Task
Estimated USD to finish one task
$0.12$0.70
Output Tokens / Task
Tokens generated per task
28K20K
Reasoning Tokens / Task
Thinking tokens burned per task
12K10K

기술 사양 (Specifications)

Architecture, release timeline, capabilities, and modalities.

FeatureMistral Small 4Claude Haiku 5.5
Official API Model ID (SDK)mistral-small-4-latestclaude-haiku-5-5-20261001
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-032026-10
Knowledge CutoffJanuary 2026August 2026
ArchitectureNext-Gen Compact Multimodal TransformerUltra-Fast Lightweight Reasoning Transformer
Parameters24BConfidential
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) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.1/1M in) across full 256K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.03/1M tokens$0.1/1M 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) · Vision (~258–765 tokens per image tile)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) · 15 GB VRAM (4-bit Quantized) · 52 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 Modalitiestext, visiontext, vision
Output Modalitiestexttext

Mistral Small 4 vs Claude Haiku 5.5: 핵심 요약 문답 (FAQ)

Which is more intelligent, Mistral Small 4 or Claude Haiku 5.5?

Claude Haiku 5.5 is more intelligent. It scores 62 compared with 48 on the composite Intelligence Index.

Which model is faster?

Claude Haiku 5.5 is faster, generating 160 tokens per second compared with 120 tokens per second.

Which model is cheaper to run?

Mistral Small 4 is cheaper at $0.07 per 1M tokens blended, compared with $0.77 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Haiku 5.5 has lower latency, with a time to first token of 0.22s compared with 0.34s.

Which model has a larger context window?

Mistral Small 4 has a larger context window, supporting 256K tokens compared with 200K tokens.

종합 평가

Verdict & Model Selection Recommendation: Choose Mistral Small 4 if your priority is High-volume agent orchestration, low-cost document parsing, and edge deployments. Its performance in demanding tasks justifies its operational token cost. Choose Claude Haiku 5.5 if your workflow prioritizes Real-time user-facing chatbots, rapid text classification, code completion, and edge agent routing. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

자주 묻는 질문 (FAQ)

How does Mistral Small 4 compare to Claude Haiku 5.5 in API token pricing and cost per token?+

Mistral Small 4 costs $0.10 per 1M input tokens and $0.30 per 1M output tokens, whereas Claude Haiku 5.5 costs $1.00 input and $5.00 output. Overall, Mistral Small 4 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.

Which model has a larger context window: Mistral Small 4 or Claude Haiku 5.5?+

Mistral Small 4 supports a context window of 256K tokens (~192k words), while Claude Haiku 5.5 supports 200K tokens (~150k words). Therefore, Mistral Small 4 can process more textual data and document context in a single prompt.

Which AI model is better for software engineering and coding: Mistral Small 4 or Claude Haiku 5.5?+

Mistral Small 4 scores 44.5% on SWE-bench Verified while Claude Haiku 5.5 scores 68.4%. For autonomous software engineering and multi-file debugging, Claude Haiku 5.5 holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Mistral Small 4 and Claude Haiku 5.5?+

Mistral Small 4 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Haiku 5.5 provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between Mistral Small 4 and Claude Haiku 5.5?+

Mistral Small 4 generates approximately 120 tokens per second, while Claude Haiku 5.5 delivers 160 tokens per second. In latency-sensitive production environments, Claude Haiku 5.5 provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Mistral Small 4 and Claude Haiku 5.5 to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Mistral Small 4 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Haiku 5.5. This tiered routing pattern cuts overall API bills by up to 70%.

AI Terminology & Guide
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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.

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