Model comparison
GLM-4.7-Flash vs Qwen3-Coder 480B-A35B Instruct
GLM-4.7-Flash and Qwen3-Coder 480B-A35B Instruct score almost the same on the Noometry Index (38.4 vs 37.7), so choose on price, context window or the category you care about most.
Last verified . 16 shared benchmarks.
Alibaba (Qwen)Summary
- They share 16 benchmarks with published results for both. GLM-4.7-Flash scores higher in 1 category and Qwen3-Coder 480B-A35B Instruct in 7 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3-Coder 480B-A35B Instruct leads 55.5 to 47.7.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $1.50 / $7.50 for Qwen3-Coder 480B-A35B Instruct.
- Qwen3-Coder 480B-A35B Instruct accepts more context: 262K tokens versus 200K.
Side by side
| GLM-4.7-Flash | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 38.4 | 37.7 |
| Released | 2026-01-19 | 2025-04 |
| Weights | Open | Open |
| Context window | 200K | 262K |
| Max output | 131K | 66K |
| Input $ / M tokens | $0.06 | $1.50 |
| Output $ / M tokens | $0.40 | $7.50 |
| Results tracked | 21 | 25 |
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Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.0 (#133), Qwen3-Coder 480B-A35B Instruct: 36.2 (#199)
| Benchmark | GLM-4.7-Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Coding | 1383 | 1413 |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| GSO | — | 4.9% |
| WeirdML | — | 41.2% |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Not comparable
GLM-4.7-Flash: —, Qwen3-Coder 480B-A35B Instruct: 23.7 (#116)
| Benchmark | GLM-4.7-Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
Reasoning Qwen3-Coder 480B-A35B Instruct leads
GLM-4.7-Flash: 20.2 (#224), Qwen3-Coder 480B-A35B Instruct: 24.7 (#141)
| Benchmark | GLM-4.7-Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1356 | 1372 |
| Kagi LLM Benchmark | — | 49.5% |
| Chess Puzzles | 0% | — |
Math Too close to call
GLM-4.7-Flash: 34.4 (#159), Qwen3-Coder 480B-A35B Instruct: 34.9 (#151)
| Benchmark | GLM-4.7-Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1354 | 1364 |
| OTIS Mock AIME 2024-2025 | 58.3% | — |
Knowledge Too close to call
GLM-4.7-Flash: 35.4 (#177), Qwen3-Coder 480B-A35B Instruct: 36.4 (#159)
| Benchmark | GLM-4.7-Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1357 | 1337 |
| GPQA Diamond | 60.5% | — |
| Vectara Hallucination Rate | 9.3% | — |
Multilingual Qwen3-Coder 480B-A35B Instruct leads
GLM-4.7-Flash: 46.8 (#152), Qwen3-Coder 480B-A35B Instruct: 47.8 (#143)
| Benchmark | GLM-4.7-Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1331 | 1345 |
| LMArena Chinese | 1403 | 1356 |
| LMArena French | 1332 | 1394 |
| LMArena German | 1336 | 1324 |
| LMArena Korean | 1284 | 1307 |
| LMArena Russian | 1333 | 1367 |
| LMArena Spanish | 1351 | 1360 |
| LMArena Japanese | — | 1309 |
Instruction Following Qwen3-Coder 480B-A35B Instruct leads
GLM-4.7-Flash: 70.3 (#162), Qwen3-Coder 480B-A35B Instruct: 71.8 (#142)
| Benchmark | GLM-4.7-Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1327 | 1356 |
Long Context Qwen3-Coder 480B-A35B Instruct leads
GLM-4.7-Flash: 40.9 (#143), Qwen3-Coder 480B-A35B Instruct: 42.0 (#126)
| Benchmark | GLM-4.7-Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1345 | 1379 |
Writing & Preference Qwen3-Coder 480B-A35B Instruct leads
GLM-4.7-Flash: 47.7 (#206), Qwen3-Coder 480B-A35B Instruct: 55.5 (#142)
| Benchmark | GLM-4.7-Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1351 | 1356 |
| LMArena Creative Writing | 1297 | 1333 |
| LMArena Multi-Turn | 1342 | 1365 |
| EQ-Bench Creative Writing | 1125 | — |
Frequently asked questions
Is GLM-4.7-Flash better than Qwen3-Coder 480B-A35B Instruct?
GLM-4.7-Flash and Qwen3-Coder 480B-A35B Instruct score almost the same on the Noometry Index (38.4 vs 37.7), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-4.7-Flash or Qwen3-Coder 480B-A35B Instruct?
GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Qwen3-Coder 480B-A35B Instruct lists at $1.50 and $7.50.
Is GLM-4.7-Flash or Qwen3-Coder 480B-A35B Instruct better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.0 versus 36.2 in the Noometry coding category.
Which has the bigger context window?
Qwen3-Coder 480B-A35B Instruct does, with 262K tokens against 200K.
How many benchmarks do GLM-4.7-Flash and Qwen3-Coder 480B-A35B Instruct share?
16 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.