GLM-4-Plus vs Yi-Large
Zhipu AI vs 01.AI · Prices checked 12 August 2026
Yi-Large is the cheaper of the two by a wide margin: $3.00 per million tokens blended against $7.00, roughly 2.3× less. A single 100K-input, 10K-output job costs $0.330 on Yi-Large against $0.770 on GLM-4-Plus.
GLM-4-Plus leads on 4 of the 4 benchmarks both models report. The widest gap is on LMArena Elo, where GLM-4-Plus leads by 45 points. GLM-4-Plus takes a 128,000-token context window against 32,000, giving 4× more room for long documents or whole-codebase work.
Pricing and capacity
| Metric | GLM-4-Plus | Yi-Large | Difference |
|---|---|---|---|
| Input / 1M tokens | $7.00 | $3.00 | 2.3× |
| Output / 1M tokens | $7.00 | $3.00 | 2.3× |
| Blended · 70/30calculated | $7.00 | $3.00 | 2.3× |
| Blended · 50/50calculated | $7.00 | $3.00 | 2.3× |
| Blended · 80/20calculated | $7.00 | $3.00 | 2.3× |
| Blended · 20/80calculated | $7.00 | $3.00 | 2.3× |
| Job cost · 100K + 10Kcalculated | $0.770 | $0.330 | 2.3× |
| Job cost · 1M + 100Kcalculated | $7.70 | $3.30 | 2.3× |
| Context window | 128,000 | 32,000 | 4.0× |
Input and output rates are as published by each provider. Blended and job-cost rows are calculated comparison metrics, not published prices — how they are derived.
Benchmarks
| Benchmark | GLM-4-Plus | Yi-Large | Leader |
|---|---|---|---|
| MMLU | 84% | 78% | GLM-4-Plus |
| MATH | 70% | 60% | GLM-4-Plus |
| HumanEval | 80% | 70% | GLM-4-Plus |
| LMArena Elo | 1244 Elo | 1199 Elo | GLM-4-Plus |
Only suites both models report are listed, so a missing score is never shown as a loss. Figures are provider-published or from public leaderboards and are not independently re-run.
What each model is for
GLM-4-Plus
Zhipu AI · Frontier
Zhipu's flagship GLM-4. Strong on Chinese-language benchmarks, with frontier-class reasoning at competitive Chinese pricing.
- Strong on Chinese benchmarks
- Tool use
- 128K context
- Tightly integrated with Zhipu cloud
Frequently asked questions
Which is cheaper, GLM-4-Plus or Yi-Large?
Yi-Large is the cheaper of the two by a wide margin: $3.00 per million tokens blended against $7.00, roughly 2.3× less. A single 100K-input, 10K-output job costs $0.330 on Yi-Large against $0.770 on GLM-4-Plus. Blended cost weights input at 70% and output at 30%; price your own token split for an exact answer, since the cheaper model on a blended basis is not always cheaper for your workload.
Which performs better, GLM-4-Plus or Yi-Large?
GLM-4-Plus leads on 4 of the 4 benchmarks both models report. The widest gap is on LMArena Elo, where GLM-4-Plus leads by 45 points. These are the figures each provider or public leaderboard publishes, not results we re-run, and a benchmark average can hide the specific behaviour your workload depends on.
Which has the larger context window, GLM-4-Plus or Yi-Large?
GLM-4-Plus takes a 128,000-token context window against 32,000, giving 4× more room for long documents or whole-codebase work. The context window caps everything in a single request: prompt, retrieved documents, conversation history and the model’s own output all share it.
Can I compare GLM-4-Plus and Yi-Large on my own numbers?
Yes. Open both in the side-by-side comparison tool to see every field at once, or use the token calculator to price your actual prompt and monthly request volume against each model. Both are free and need no sign-up.
Price it for your own workload
Related matchups
Terms used on this page
Prices and scores are recomputed on every deploy from the catalogue. Prices checked 12 August 2026.