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Granite 4.1 8B vs GLM 4.7 Flash

Detailed technical comparison between Granite 4.1 8B (IBM) 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

Granite 4.1 8B: 1 WinvsGLM 4.7 Flash: 5 Wins
Context Leader

GLM 4.7 Flash

202,752 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

Granite 4.1 8B

$0.05 / MTok
IBMactive

Granite 4.1 8B

Granite 4.1 8B is a dense, decoder-only 8-billion-parameter language model from IBM, part of the Granite 4.1 family. It supports a 131K-token context window and is designed for enterprise tasks...

View Granite 4.1 8B 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
SpecificationGranite 4.1 8BGLM 4.7 Flash
ProviderIBMZhipu AI
Context Window131,072 tokens202,752 tokens🏆
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-302026-01-19

API Pricing Comparison

Input Price per Million Tokens

Granite 4.1 8B

$0.05

GLM 4.7 Flash

$0.06

Output Price per Million Tokens

Granite 4.1 8B

$0.10

GLM 4.7 Flash

$0.40

💡 Cost Ratio: Granite 4.1 8B is 1.2x cheaper per input token than GLM 4.7 Flash.

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
75.4%vs77.2%+1.8% GLM 4.7 Flash
Granite 4.1 8B
GLM 4.7 Flash 🏆
HumanEvalPython coding & logic synthesis
71.6%vs78.5%+6.9% GLM 4.7 Flash
Granite 4.1 8B
GLM 4.7 Flash 🏆
MATHComplex mathematical problem solving
41.4%vs40.0%+1.4% Granite 4.1 8B
Granite 4.1 8B 🏆
GLM 4.7 Flash
GPQAGraduate-level expert reasoning
28.8%vs31.0%+2.2% GLM 4.7 Flash
Granite 4.1 8B
GLM 4.7 Flash 🏆
HellaSwagCommonsense reasoning and inference
76.0%vs80.0%+4.0% GLM 4.7 Flash
Granite 4.1 8B
GLM 4.7 Flash 🏆
MT-BenchMulti-turn conversation flow quality
7.9%vs8.1%+0.2% GLM 4.7 Flash
Granite 4.1 8B
GLM 4.7 Flash 🏆

Granite 4.1 8B Quirks & Gotchas

No developer gotchas reported.

GLM 4.7 Flash Quirks & Gotchas

No developer gotchas reported.

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