Model comparison
GLM-4.7-Flash vs Phi-4
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 31.2 on the Noometry Index. Phi-4 costs 1.7× less per token, which makes it the better buy when GLM-4.7-Flash's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
MicrosoftSummary
- They share 20 benchmarks with published results for both. GLM-4.7-Flash scores higher in 8 categories and Phi-4 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-4.7-Flash leads 36.1 to 20.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 13.8% for Phi-4.
- Phi-4 is cheaper at $0.07 / $0.14 per million input/output tokens, against $0.06 / $0.40 for GLM-4.7-Flash.
- GLM-4.7-Flash accepts more context: 200K tokens versus 128K.
Side by side
| GLM-4.7-Flash | Phi-4 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Microsoft |
| Noometry Index | 38.8 | 31.2 |
| Released | 2026-01-19 | 2024-12-11 |
| Weights | Open | Open |
| Context window | 200K | 128K |
| Max output | 131K | 4K |
| Input $ / M tokens | $0.06 | $0.07 |
| Output $ / M tokens | $0.40 | $0.14 |
| Results tracked | 21 | 37 |
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Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.6 (#135), Phi-4: 34.4 (#239)
| Benchmark | GLM-4.7-Flash | Phi-4 |
|---|---|---|
| LMArena Coding | 1383 | 1231 |
| BigCodeBench Instruct | — | 45.5% |
| LiveBench Coding | — | 30.7% |
| BigCodeBench Complete | — | 55.4% |
Agentic & Tool Use Not comparable
GLM-4.7-Flash: —, Phi-4: 22.8 (#128)
| Benchmark | GLM-4.7-Flash | Phi-4 |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.8% |
| BALROG | — | 11.6% |
Reasoning GLM-4.7-Flash leads
GLM-4.7-Flash: 20.9 (#229), Phi-4: 17.7 (#291)
| Benchmark | GLM-4.7-Flash | Phi-4 |
|---|---|---|
| Chess Puzzles | 0% | 1% |
| LMArena Hard Prompts | 1356 | 1220 |
| LiveBench Reasoning | — | 47.8% |
| LiveBench Data Analysis | — | 45.2% |
| Epoch Capabilities Index | — | 130.42 |
| LiveBench | — | 41.6% |
Math GLM-4.7-Flash leads
GLM-4.7-Flash: 36.1 (#173), Phi-4: 20.8 (#285)
| Benchmark | GLM-4.7-Flash | Phi-4 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | 13.8% |
| LMArena Math | 1355 | 1246 |
| LiveBench Math | — | 42% |
| MATH Level 5 | — | 64.9% |
Knowledge GLM-4.7-Flash leads
GLM-4.7-Flash: 35.5 (#184), Phi-4: 32.6 (#209)
| Benchmark | GLM-4.7-Flash | Phi-4 |
|---|---|---|
| GPQA Diamond | 60.5% | 56.1% |
| Vectara Hallucination Rate | 9.3% | 3.7% |
| LMArena Expert | 1357 | 1203 |
| Confabulations | — | 29.4% |
| MMLU | — | 84.8% |
Multilingual GLM-4.7-Flash leads
GLM-4.7-Flash: 46.5 (#158), Phi-4: 37.2 (#237)
| Benchmark | GLM-4.7-Flash | Phi-4 |
|---|---|---|
| LMArena Non-English | 1330 | 1197 |
| LMArena Chinese | 1403 | 1212 |
| LMArena French | 1332 | 1224 |
| LMArena German | 1337 | 1222 |
| LMArena Korean | 1283 | 1151 |
| LMArena Russian | 1332 | 1209 |
| LMArena Spanish | 1350 | 1234 |
| LMArena Japanese | — | 1158 |
Instruction Following GLM-4.7-Flash leads
GLM-4.7-Flash: 70.1 (#167), Phi-4: 60.4 (#251)
| Benchmark | GLM-4.7-Flash | Phi-4 |
|---|---|---|
| LMArena Instruction Following | 1327 | 1201 |
| LiveBench Instruction Following | — | 58.4% |
Long Context GLM-4.7-Flash leads
GLM-4.7-Flash: 40.9 (#148), Phi-4: 36.9 (#226)
| Benchmark | GLM-4.7-Flash | Phi-4 |
|---|---|---|
| LMArena Longer Query | 1345 | 1217 |
Writing & Preference GLM-4.7-Flash leads
GLM-4.7-Flash: 47.4 (#210), Phi-4: 40.5 (#244)
| Benchmark | GLM-4.7-Flash | Phi-4 |
|---|---|---|
| LMArena Text | 1351 | 1217 |
| LMArena Creative Writing | 1297 | 1182 |
| LMArena Multi-Turn | 1342 | 1206 |
| Short-Story Creative Writing | — | 62.6% |
| EQ-Bench Creative Writing | 1125 | — |
| LiveBench Language | — | 25.6% |
Frequently asked questions
Is GLM-4.7-Flash better than Phi-4?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 31.2 on the Noometry Index. Phi-4 costs 1.7× less per token, which makes it the better buy when GLM-4.7-Flash's lead doesn't matter for your workload.
Which is cheaper, GLM-4.7-Flash or Phi-4?
Phi-4 is cheaper. It lists at $0.07 per million input tokens and $0.14 per million output tokens; GLM-4.7-Flash lists at $0.06 and $0.40.
Is GLM-4.7-Flash or Phi-4 better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
GLM-4.7-Flash does, with 200K tokens against 128K.
How many benchmarks do GLM-4.7-Flash and Phi-4 share?
20 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Phi-4 has 37.