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Jamba Large 1.7 vs GLM 4.7 Flash

Detailed technical comparison between Jamba Large 1.7 (AI21 Labs) and GLM 4.7 Flash (Zhipu AI). 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: 6 WinsvsGLM 4.7 Flash: 0 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

GLM 4.7 Flash

$0.06 / 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 →
Zhipu AIactive

GLM 4.7 Flash

As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...

View GLM 4.7 Flash Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationJamba Large 1.7GLM 4.7 Flash
ProviderAI21 LabsZhipu AI
Context Window256,000 tokens🏆202,752 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 Date2025-08-082026-01-19

API Pricing Comparison

Input Price per Million Tokens

Jamba Large 1.7

$2.00

GLM 4.7 Flash

$0.06

Output Price per Million Tokens

Jamba Large 1.7

$8.00

GLM 4.7 Flash

$0.40

💡 Cost Ratio: GLM 4.7 Flash is 33.3x cheaper per input token than Jamba Large 1.7.

Want to test both models live?

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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%vs77.2%+10.6% Jamba Large 1.7
Jamba Large 1.7 🏆
GLM 4.7 Flash
HumanEvalPython coding & logic synthesis
87.0%vs78.5%+8.5% Jamba Large 1.7
Jamba Large 1.7 🏆
GLM 4.7 Flash
MATHComplex mathematical problem solving
68.2%vs40.0%+28.2% Jamba Large 1.7
Jamba Large 1.7 🏆
GLM 4.7 Flash
GPQAGraduate-level expert reasoning
49.6%vs31.0%+18.6% Jamba Large 1.7
Jamba Large 1.7 🏆
GLM 4.7 Flash
HellaSwagCommonsense reasoning and inference
85.4%vs80.0%+5.4% Jamba Large 1.7
Jamba Large 1.7 🏆
GLM 4.7 Flash
MT-BenchMulti-turn conversation flow quality
9.1%vs8.1%+1.0% Jamba Large 1.7
Jamba Large 1.7 🏆
GLM 4.7 Flash

Jamba Large 1.7 Quirks & Gotchas

No developer gotchas reported.

GLM 4.7 Flash Quirks & Gotchas

No developer gotchas reported.

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