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GLM 4.7 vs R1 Distill Llama 70B

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for GLM 4.7 and R1 Distill Llama 70B.

Zhipu AI

GLM 4.7

GLM-4.7 is Z.aiโ€™s latest flagship model, featuring upgrades in two key areas: enhanced programming capabilities and more stable multi-step reasoning/execution. It demonstrates significant improvements in executing complex agent tasks while...

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DeepSeek

R1 Distill Llama 70B

DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across...

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Technical Specifications

SpecificationGLM 4.7R1 Distill Llama 70B
ProviderZhipu AIDeepSeek
Context Window202,752 tokens128,000 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-12-222025-01-23

API Pricing Comparison

Input Price per Million Tokens

GLM 4.7

$0.40

R1 Distill Llama 70B

$0.80

Output Price per Million Tokens

GLM 4.7

$1.75

R1 Distill Llama 70B

$0.80

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8150.0%vs8520.0%
GLM 4.7
R1 Distill Llama 70B
HumanEvalPython coding & logic synthesis
8200.0%vs8830.0%
GLM 4.7
R1 Distill Llama 70B
MATHComplex mathematical problem solving
5150.0%vs7000.0%
GLM 4.7
R1 Distill Llama 70B
GPQAGraduate-level expert reasoning
3800.0%vs4450.0%
GLM 4.7
R1 Distill Llama 70B
HellaSwagCommonsense reasoning and inference
8350.0%vs8600.0%
GLM 4.7
R1 Distill Llama 70B
MT-BenchMulti-turn conversation flow quality
865.0%vs905.0%
GLM 4.7
R1 Distill Llama 70B

GLM 4.7 Quirks & Gotchas

No developer gotchas reported.

R1 Distill Llama 70B Quirks & Gotchas

No developer gotchas reported.