Mistral Small 4 vs Claude Haiku 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Mistral Small 4 dari Mistral AI dan Claude Haiku 5.5 dari Anthropic adalah dua model AI unggulan. Mistral Small 4 menawarkan jendela konteks 256K token dengan harga $0.10/$0.30 per 1 juta token, sedangkan Claude Haiku 5.5 menyediakan konteks 200K token seharga $1.00/$5.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Mistral Small 4
Inferensi Super CepatMistral Small 4 dari Mistral AI adalah model AI yang dirancang untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, menghadirkan jendela konteks 256K, kecepatan 120 token/detik, indeks kecerdasan 48/100, sert
$0.10 / 1M
$0.30 / 1M
256K tokens
44.5%
Claude Haiku 5.5
Inferensi Super CepatClaude Haiku 5.5 dari Anthropic adalah model AI yang dirancang untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, menghadirkan jendela konteks 200K, kecepatan 160 token/detik, indeks kecerdasan 62/100, sert
$1.00 / 1M
$5.00 / 1M
200K tokens
68.4%
Perbedaan Utama Sekilas
- 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%).
| Feature | Mistral Small 4 | Claude Haiku 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 48 | 62 |
Provider | Mistral AI | Anthropic |
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 text | 200K tokens~300 A4 pages of text |
Max Output Tokens Per single request | 16K | 64K |
Throughput Speed Tokens generated per second | 120 tok/s | 160 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 |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor Benchmark Terverifikasi
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Mistral Small 4 · Strengths & Key Advantages
- Jendela konteks 256K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 44.5% · GPQA Diamond 56%)
- Kecepatan generasi tinggi 120 token/detik dengan latensi token pertama (TTFT) hanya 340 ms
- Bobot terbuka (24B) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama
Considerations & Trade-offs
- Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
Claude Haiku 5.5 · Strengths & Key Advantages
- Jendela konteks 200K dengan kapasitas output maksimum hingga 64K token (SWE-bench Verified 68.4% · GPQA Diamond 69.8%)
- Kecepatan generasi tinggi 160 token/detik dengan latensi token pertama (TTFT) hanya 220 ms
- Skema harga API kompetitif (tarif $1/$5 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
- Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Mistral Small 4 | Claude Haiku 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.12 | $0.70 |
Output Tokens / Task Tokens generated per task | 28K | 20K |
Reasoning Tokens / Task Thinking tokens burned per task | 12K | 10K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Mistral Small 4 | Claude Haiku 5.5 |
|---|---|---|
| Official API Model ID (SDK) | mistral-small-4-latest | claude-haiku-5-5-20261001 |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-03 | 2026-10 |
| Knowledge Cutoff | January 2026 | August 2026 |
| Architecture | Next-Gen Compact Multimodal Transformer | Ultra-Fast Lightweight Reasoning Transformer |
| Parameters | 24B | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 4,000 – 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 window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.03/1M tokens | $0.1/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| Multimodal Token Billing | Text 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 VRAM | BF16 / 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 Classification | Open-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 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text, vision |
| Output Modalities | text | text |
Mistral Small 4 vs Claude Haiku 5.5: Jawaban Cepat (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.
Kesimpulan
Baik Mistral Small 4 (Sangat cocok untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Claude Haiku 5.5 (Sangat cocok untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Claude Haiku 5.5 unggul dalam penalaran dan pemrograman, Claude Haiku 5.5 memberikan kecepatan generasi token lebih tinggi, dan Mistral Small 4 lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Mistral Small 4 atau Claude Haiku 5.5?+
Dalam indeks kecerdasan gabungan dan benchmark coding, Claude Haiku 5.5 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Mistral Small 4 vs Claude Haiku 5.5?+
Mistral Small 4 mengenakan biaya $0.10 / $0.30 per 1M token input/output, sedangkan Claude Haiku 5.5 sebesar $1.00 / $5.00. Secara keseluruhan, Mistral Small 4 lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Mistral Small 4 mendukung konteks 256K token dibandingkan 200K token pada Claude Haiku 5.5, sementara Claude Haiku 5.5 unggul dalam kecepatan output token per detik.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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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.
Sumber resmi: Dokumentasi API resmi Mistral AI & Anthropic serta evaluasi benchmark independen (2026).