Qwen3.5 397B-A17B vs o3 vs GLM-5
Qwen3.5 397B-A17B comes out ahead, 65 to 58 and 55 on our weighted score, and it is the cheaper option too.
- Our pick
Alibaba (Qwen)Qwen3.5 397B-A17B
65/100- ECI146.7
- Price$0.60 / $3.60
- Context262K
OpenAIo3
58/100- ECI146.9
- Price$2.00 / $8.00
- Context200K
Z.ai (Zhipu)GLM-5
55/100- ECI145.8
- Price$1.00 / $3.20
- Context205K
Qwen3.5 397B-A17B is our pick
Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against o3 (58) and GLM-5 (55). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- Capabilityo3Capabilities Index (ECI): o3 146.9 · Qwen3.5 397B-A17B 146.7 · GLM-5 145.8
- Lowest priceQwen3.5 397B-A17BQwen3.5 397B-A17B $1.35 · GLM-5 $1.55 · o3 $3.50 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 397B-A17BQwen3.5 397B-A17B 262,144 · GLM-5 204,800 · o3 200,000 tokens
- Widest inputsQwen3.5 397B-A17BQwen3.5 397B-A17B: Text, Images, Audio, Video · o3: Text, Images, PDFs · GLM-5: Text
- Self-hostingQwen3.5 397B-A17B and GLM-5Publishes downloadable weights
| Measure | Weight | Qwen3.5 397B-A17B | o3 | GLM-5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 74 | 74 | 73 |
| Price | 25% | 44 | 24 | 41 |
| Inputs & features | 15% | 90 | 80 | 35 |
| Context window | 10% | 37 | 32 | 32 |
| Overall | 100% | 65/100 | 58/100 | 55/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.5 397B-A17BAlibaba (Qwen) | o3OpenAI | GLM-5Z.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 146.7 | 146.9 (best) | 145.8 |
| ECI rank | #67 of 148 | #63 of 148 (best) | #74 of 148 |
| GPQA DiamondGraduate-level science questions | 86.4% | 81.8% | 87.8% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 31.2% | 33.3% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 88.9% (best) | 84.4% | 80.0% |
| SWE-bench VerifiedFixing real GitHub issues | — | 62.3% | 72.1% (best) |
| SimpleQA VerifiedShort factual questions | — | 49.4% | — |
| Price per million tokens | |||
| Input | $0.60 (best) | $2.00 | $1.00 |
| Output | $3.60 | $8.00 | $3.20 (best) |
| Cached input | — | $0.50 | $0.20 (best) |
| Blended (3:1) | $1.35 (best) | $3.50 | $1.55 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official OpenAI API | Official Z.AI API |
| Limits | |||
| Context window | 262,144 tokens (best) | 200,000 tokens | 204,800 tokens |
| Max output | 65,536 tokens | 100,000 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | Yes | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | qwen3.5-397b-a17b | o3 | glm-5 |
| API providers | 23 | 18 | 27 (best) |
| Released | Feb 15, 2026 | Apr 16, 2025 | Feb 12, 2026 |
| Knowledge cutoff | — | May 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3.5 397B-A17B$13.20
- o3$36.00
- GLM-5$16.40
Which should you choose?
Which is better: Qwen3.5 397B-A17B, o3 or GLM-5?
Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against o3 (58) and GLM-5 (55). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3.5 397B-A17B, o3 or GLM-5?
Qwen3.5 397B-A17B is cheaper at $0.60 input / $3.60 output per million tokens (official Alibaba API price). GLM-5 costs $1.00 input / $3.20 output per million tokens (official Z.AI API price); o3 costs $2.00 input / $8.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $1.35 per million tokens for Qwen3.5 397B-A17B versus $1.55 for GLM-5 (1.1× as much) and $3.50 for o3 (2.6× as much).
Which scores higher on benchmarks?
o3 scores higher on the Capabilities Index (ECI): o3 146.9 (#63 of 148), Qwen3.5 397B-A17B 146.7 (#67 of 148) and GLM-5 145.8 (#74 of 148). The confidence ranges of the top two overlap (144.9–148.6 vs 144.8–148.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5 87.8%, Qwen3.5 397B-A17B 86.4%, o3 81.8%; OTIS Mock AIME 2024–2025 — Qwen3.5 397B-A17B 88.9%, o3 84.4%, GLM-5 80.0%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 397B-A17B yet, so there is no like-for-like coding score. On overall capability, o3 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.5 397B-A17B has the largest context window at 262,144 tokens, against 204,800 for GLM-5 and 200,000 for o3. Maximum output per response: Qwen3.5 397B-A17B up to 65,536, o3 up to 100,000, GLM-5 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Qwen3.5 397B-A17B accepts text, images, audio and video; o3 accepts text, images and PDFs; GLM-5 accepts text. Qwen3.5 397B-A17B handles the widest range of inputs.
Are any of these open source?
Qwen3.5 397B-A17B and GLM-5 publishes its weights and can be self-hosted; o3 is proprietary.
Which is newer?
Qwen3.5 397B-A17B is the newest, released Feb 15, 2026. GLM-5 came out Feb 12, 2026; o3 came out Apr 16, 2025. Knowledge cutoff: o3 May 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
