GLM-4 9B Chat vs Qwen2.5 7B: Benchmark Comparison
Detailed comparison of GLM-4 9B Chat and Qwen2.5 7B covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | GLM-4 9B Chat | Qwen2.5 7B |
|---|---|---|
| Vendor | other | alibaba |
| Version | glm-4-9b-chat | 2.5-7b |
| Release Date | 2024-06-05 | 2024-09-19 |
| Context Window | 131072 tokens | 131072 tokens |
| Input Modalities | text, image | text |
| Output Modalities | text | text |
| License | GLM-4 License | Qwen License |
| SOC2 | ✗ | ✗ |
| HIPAA | ✗ | ✗ |
| GDPR | ✗ | ✗ |
| ISO 27001 | ✗ | ✗ |
Benchmark Results
| Benchmark | GLM-4 9B Chat | Qwen2.5 7B | Winner |
|---|---|---|---|
| ARC | 88.6 | 88.4 | GLM-4 9B Chat |
| BBH | 67.2 | 61.9 | GLM-4 9B Chat |
| GPQA | 37.2 | 28.5 | GLM-4 9B Chat |
| GSM8K | 58 | 63.7 | Qwen2.5 7B |
| HUMANEVAL | 62.9 | 66.5 | Qwen2.5 7B |
| IFEVAL | 59.9 | 55.4 | GLM-4 9B Chat |
| MATH | 26.6 | 41.9 | Qwen2.5 7B |
| MMLU | 70.7 | 73.6 | Qwen2.5 7B |
| MUSR | 49.5 | 46.9 | GLM-4 9B Chat |
| WINOGRANDE | 79.4 | 71.4 | GLM-4 9B Chat |
Pricing Comparison
| Tier (per Mtok) | GLM-4 9B Chat | Qwen2.5 7B |
|---|---|---|
| Input | $0.18 | $0.15 |
| Output | $0.18 | $0.15 |
| Cache Read | $0 | $0 |
| Cache Write | $0 | $0 |
GLM-4 9B Chat contre Qwen2.5 7B
Aperçu du modèle
GLM-4 9B Chat and Qwen2.5 7B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
Spécifications clés
| Fournisseur | Date de sortie | Fenêtre de contexte | Licence |
|---|---|---|---|
| Other / Alibaba | 2024-06-05 / 2024-09-19 | 131K / 131K | GLM-4 License / Qwen License |
Performance aux benchmarks
| Benchmark | GLM-4 9B Chat | Qwen2.5 7B | Gagnant |
|---|---|---|---|
| ARC | 88.6 | 88.4 | Tie |
| BBH (BIG-Bench Hard) | 67.2 | 61.9 | A |
| GPQA | 37.2 | 28.5 | A |
| GSM8K (Grade School Math 8K) | 58.0 | 63.7 | B |
| HumanEval | 62.9 | 66.5 | B |
| IFEval | 59.9 | 55.4 | A |
| MATH | 26.6 | 41.9 | B |
| MMLU (Massive Multitask Language Understanding) | 70.7 | 73.6 | B |
| MUSR | 49.5 | 46.9 | A |
| WinoGrande | 79.4 | 71.4 | A |
Comparaison des prix
| Entrée | Sortie | Lecture cache | Écriture cache |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
par million de jetons — A / B
Forces & Faiblesses
GLM-4 9B Chat
- ✅ 支持文本、图像、音频多模态输入。
- ⚠️ 闭源专有模型，不支持自托管。
Qwen2.5 7B
- ✅ 可靠的通用模型。
- ⚠️ 闭源专有模型，不支持自托管。
Avis de la rédaction
GLM-4 9B Chat and Qwen2.5 7B each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.
FAQ
Which model is better for coding tasks?
Refer to the HumanEval benchmark table; the model with a higher score is better suited for coding tasks.
Which model is cheaper?
Refer to the pricing comparison table above; the model with lower input/output prices is more cost-effective.
Which has a longer context window?
Refer to the key specifications table; the model with a larger context window is better for long documents.
Références
Editor's Take
See Editor's Take section.