Head-to-Head Model Comparison

Jamba 1.5 Mini vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
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AI21Anthropicopen-sourceflagship

Compare Jamba 1.5 Mini by AI21 against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Head-to-Head Comparison

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AI21

Jamba 1.5 Mini

Fast SSM-Transformer Hybrid

Compact hybrid Mamba-Transformer model activating only 12B parameters per token while sustaining a 256K context window with remarkable speed.

Intelligence Index39 / 100
Input Token:

$0.20 / 1M

Output Token:

$0.40 / 1M

Context Window:

256K tokens

SWE-bench Verified:

35.8%

Anthropic

Claude Opus 5.5

Frontier Intelligence Titan

Anthropic's most intelligent model for complex reasoning, research, and strategic analysis.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Key Differences at a Glance

  • Jamba 1.5 Mini is 33.5x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 256K tokens).
  • Jamba 1.5 Mini is faster at 120 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 35.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureJamba 1.5 MiniClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
3994
Provider
AI21Anthropic
Input Price
Cost per million input tokens
$0.20 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$0.40 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.11 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
4K128K
Throughput Speed
Tokens generated per second
120 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
35.8%84.6%
GPQA Diamond
Graduate-level reasoning
44.2%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.05 / 1M$0.40 / 1M

Who Wins Where?

At-a-glance decision framework
Coding
Claude Opus 5.5
+48.8% SWE-bench lead
Cost
Jamba 1.5 Mini
33.5x cheaper monthly runtime
Speed
Jamba 1.5 Mini
+54% faster generation
Context
Claude Opus 5.5
1M tokens window

Empirical Head-to-Head Benchmark Scores

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

Jamba 1.5 MiniClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

35.8%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

44.2%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

64%vs91.5%
LMSYS Chatbot Arena Elo

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

1242ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

4.8%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

21.5%vs66.4%
SciCode (Scientific Computing)

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

22.8%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

37.5%vs83.1%
AIME (Advanced Math Competition)

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

45%vs95.4%
Long-Context Reasoning

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

72%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

120 tok/s vs78 tok/s

Latency & Response Time

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
Jamba 1.5 Mini0.34s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Jamba 1.5 Mini4.51s
Claude Opus 5.57.81s

Real-Time Interactive Token Cost 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)
Jamba 1.5 Mini Monthly API Bill
$0.74 / month
$0.2/1M in · $0.4/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Jamba 1.5 Mini saves approximately $23.87 / month (97%) under this workload.33.5x Savings

Jamba 1.5 Mini · Strengths & Key Advantages

  • Activates only 12B parameters per token, delivering very high generation throughput
  • Full 256K context window on single server nodes
  • Openly accessible weights under AI21 open license
  • Ultra-affordable API pricing ($0.20 input / $0.40 output)
Considerations & Trade-offs
  • Modest coding capability compared to dedicated coding models
  • 4K max output cap

Claude Opus 5.5 · Strengths & Key Advantages

  • Unmatched autonomous multi-step agentic coding and refactoring
  • Flawless multi-document reasoning over 1M token context with no long-prompt surcharge
  • Highest composite Intelligence Index score measured (94/100), leading SWE-bench Verified at 84.6%
  • Precise tool execution with robust error-recovery loops
Considerations & Trade-offs
  • Premium output pricing ($20.00/M) plus heavy reasoning-token usage (~68K output tokens per complex task) keeps long agentic runs expensive
  • Long thinking times at maximum effort can push a single hard agentic task toward ~$3.85+

Token Use & Task Economics

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

MetricJamba 1.5 MiniClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.12$3.85
Output Tokens / Task
Tokens generated per task
20K68K
Reasoning Tokens / Task
Thinking tokens burned per task
0K42K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

FeatureJamba 1.5 MiniClaude Opus 5.5
Official API Model ID (SDK)jamba-1-5-miniclaude-opus-5-5-20260901
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2024-082026-09
Knowledge CutoffMarch 2024June 2026
ArchitectureHybrid SSM-Transformer (Mamba + Transformer MoE)Extended Autonomous Hybrid Reasoning Transformer
Parameters52B (12B active)Confidential
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 ($0.2/1M in) across full 256K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.05/1M 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) · 32 GB VRAM (4-bit Quantized) · 112 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

Jamba 1.5 Mini vs Claude Opus 5.5: Quick Answers

Which is more intelligent, Jamba 1.5 Mini or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 39 on the composite Intelligence Index.

Which model is faster?

Jamba 1.5 Mini is faster, generating 120 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Jamba 1.5 Mini is cheaper at $0.11 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Jamba 1.5 Mini has lower latency, with a time to first token of 0.34s 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 256K tokens.

Verdict

Choose Jamba 1.5 Mini for cost-effective long-document processing, customer dialogue logging, and high-speed retrieval, or choose Claude Opus 5.5 for large-scale software development agents, enterprise codebases, and mission-critical scientific synthesis.

Frequently asked questions

Which is cheaper: Jamba 1.5 Mini or Claude Opus 5.5?+

Jamba 1.5 Mini costs $0.2/1M input and $0.4/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Jamba 1.5 Mini or Claude Opus 5.5?+

Jamba 1.5 Mini supports 256K 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.

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.

Sources: AI21 & Anthropic Official Documentation