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Jamba Large 1.7 vs GPT-5.2-Codex

Detailed technical comparison between Jamba Large 1.7 (AI21 Labs) and GPT-5.2-Codex (OpenAI). 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

Jamba Large 1.7: 0 WinsvsGPT-5.2-Codex: 6 Wins
Context Leader

GPT-5.2-Codex

400,000 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

GPT-5.2-Codex

$1.75 / MTok
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 →
OpenAIactive

GPT-5.2-Codex

GPT-5.2-Codex is an upgraded version of GPT-5.1-Codex optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....

View GPT-5.2-Codex Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationJamba Large 1.7GPT-5.2-Codex
ProviderAI21 LabsOpenAI
Context Window256,000 tokens400,000 tokens🏆
Agent SuitabilityNot yet benchmarkedNot yet benchmarked
Time to First Token (TTFT)No public TTFT dataNo public TTFT data
Deployment Modelmanaged apimanaged api
Production StabilityStable GA (est.)Stable GA (est.)
API AvailableYesYes
Released Date2025-08-082026-01-14

API Pricing Comparison

Input Price per Million Tokens

Jamba Large 1.7

$2.00

GPT-5.2-Codex

$1.75

Output Price per Million Tokens

Jamba Large 1.7

$8.00

GPT-5.2-Codex

$14.00

💡 Cost Ratio: GPT-5.2-Codex is 1.1x 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
87.8%vs93.0%+5.2% GPT-5.2-Codex
Jamba Large 1.7
GPT-5.2-Codex 🏆
HumanEvalPython coding & logic synthesis
87.0%vs99.0%+12.0% GPT-5.2-Codex
Jamba Large 1.7
GPT-5.2-Codex 🏆
MATHComplex mathematical problem solving
68.2%vs81.4%+13.2% GPT-5.2-Codex
Jamba Large 1.7
GPT-5.2-Codex 🏆
GPQAGraduate-level expert reasoning
49.6%vs56.4%+6.8% GPT-5.2-Codex
Jamba Large 1.7
GPT-5.2-Codex 🏆
HellaSwagCommonsense reasoning and inference
85.4%vs88.6%+3.2% GPT-5.2-Codex
Jamba Large 1.7
GPT-5.2-Codex 🏆
MT-BenchMulti-turn conversation flow quality
9.1%vs9.5%+0.3% GPT-5.2-Codex
Jamba Large 1.7
GPT-5.2-Codex 🏆

Jamba Large 1.7 Quirks & Gotchas

No developer gotchas reported.

GPT-5.2-Codex Quirks & Gotchas

No developer gotchas reported.

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