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GPT-4o-mini vs Jamba Large 1.7

Detailed technical comparison between GPT-4o-mini (OpenAI) and Jamba Large 1.7 (AI21 Labs). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.

⚡ Executive Summary & Verdict

Comparison Snapshot

GPT-4o-mini: 1 WinvsJamba Large 1.7: 5 Wins
Context Leader

Jamba Large 1.7

256,000 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

GPT-4o-mini

$0.15 / MTok
OpenAIactive

GPT-4o-mini

GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...

View GPT-4o-mini Full Specs →
AI21 Labsactive

Jamba Large 1.7

Jamba Large 1.7 is the latest model in the Jamba open family, offering improvements in grounding, instruction-following, and overall efficiency. Built on a hybrid SSM-Transformer architecture with a 256K context...

View Jamba Large 1.7 Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationGPT-4o-miniJamba Large 1.7
ProviderOpenAIAI21 Labs
Context Window128,000 tokens256,000 tokens🏆
Agent Suitability82/100N/A
Time to First Token (TTFT)150 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-07-182025-08-08

API Pricing Comparison

Input Price per Million Tokens

GPT-4o-mini

$0.15

Jamba Large 1.7

$2.00

Output Price per Million Tokens

GPT-4o-mini

$0.60

Jamba Large 1.7

$8.00

💡 Cost Ratio: GPT-4o-mini is 13.3x cheaper per input token than Jamba Large 1.7.

Want to test both models live?

Run side-by-side prompt benchmarks in our dynamic multi-model Sandbox. Compare execution speeds, latency metrics, and compute actual costs in real-time.

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Benchmark Performance Metrics

Standardized Scores (0–100%)

Scores show verified raw accuracy percentages across standardized AI evaluation suites. Higher bars indicate superior performance in that domain.

MMLUGeneral knowledge & multi-task understanding
82.0%vs87.8%+5.8% Jamba Large 1.7
GPT-4o-mini
Jamba Large 1.7 🏆
HumanEvalPython coding & logic synthesis
84.0%vs87.0%+3.0% Jamba Large 1.7
GPT-4o-mini
Jamba Large 1.7 🏆
MATHComplex mathematical problem solving
70.2%vs68.2%+2.0% GPT-4o-mini
GPT-4o-mini 🏆
Jamba Large 1.7
GPQAGraduate-level expert reasoning
45.0%vs49.6%+4.6% Jamba Large 1.7
GPT-4o-mini
Jamba Large 1.7 🏆
HellaSwagCommonsense reasoning and inference
84.7%vs85.4%+0.7% Jamba Large 1.7
GPT-4o-mini
Jamba Large 1.7 🏆
MT-BenchMulti-turn conversation flow quality
8.6%vs9.1%+0.5% Jamba Large 1.7
GPT-4o-mini
Jamba Large 1.7 🏆

GPT-4o-mini Quirks & Gotchas

  • ▸Ultra-low latency — best TTFT in the OpenAI lineup
  • ▸Tool calling limited to single-step — not suitable for complex agentic pipelines

Jamba Large 1.7 Quirks & Gotchas

No developer gotchas reported.

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