GLM-5 vs Nemotron 3.5 Lightning 30B A3B vs Qwen3.5 397B-A17B
Nemotron 3.5 Lightning 30B A3B comes out ahead, 71 to 56 and 37 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-5
37/100- ECI145.8
- Price$1.00 / $3.20
- Context205K
- Our pick
NVIDIANemotron 3.5 Lightning 30B A3B
71/100- ECI—
- Price$0.05 / $0.20
- Context262K
Alibaba (Qwen)Qwen3.5 397B-A17B
56/100- ECI146.7
- Price$0.60 / $3.60
- Context262K
Nemotron 3.5 Lightning 30B A3B is our pick
Nemotron 3.5 Lightning 30B A3B is the better all-round choice, scoring 71/100 against Qwen3.5 397B-A17B (56) and GLM-5 (37). It leads on price. Qwen3.5 397B-A17B wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceNemotron 3.5 Lightning 30B A3BNemotron 3.5 Lightning 30B A3B $0.087 · Qwen3.5 397B-A17B $1.35 · GLM-5 $1.55 per 1M tokens (3:1 blend)
- Longest contextNemotron 3.5 Lightning 30B A3B and Qwen3.5 397B-A17BNemotron 3.5 Lightning 30B A3B 262,144 · Qwen3.5 397B-A17B 262,144 · GLM-5 204,800 tokens
- Widest inputsQwen3.5 397B-A17BGLM-5: Text · Nemotron 3.5 Lightning 30B A3B: Text · Qwen3.5 397B-A17B: Text, Images, Audio, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-5 | Nemotron 3.5 Lightning 30B A3B | Qwen3.5 397B-A17B |
|---|---|---|---|---|
| Price | 50% | 41 | 100 | 44 |
| Inputs & features | 30% | 35 | 45 | 90 |
| Context window | 20% | 32 | 37 | 37 |
| Overall | 100% | 37/100 | 71/100 | 56/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5Z.ai (Zhipu) | Nemotron 3.5 Lightning 30B A3BNVIDIA | Qwen3.5 397B-A17BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 145.8 | — | 146.7 (best) |
| ECI rank | #74 of 148 | — | #67 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 87.8% (best) | — | 86.4% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 31.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 80.0% | — | 88.9% (best) |
| SWE-bench VerifiedFixing real GitHub issues | 72.1% | — | — |
| Price per million tokens | |||
| Input | $1.00 | $0.05 (best) | $0.60 |
| Output | $3.20 | $0.20 (best) | $3.60 |
| Cached input | $0.20 | — | — |
| Blended (3:1) | $1.55 | $0.087 (best) | $1.35 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 9 providers | Official Alibaba API |
| Limits | |||
| Context window | 204,800 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 131,072 tokens | 262,144 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | glm-5 | nvidia/nemotron-3.5-lightning-30b-a3b | qwen3.5-397b-a17b |
| API providers | 27 (best) | 12 | 23 |
| Released | Feb 12, 2026 | Aug 11, 2026 | Feb 15, 2026 |
| Knowledge cutoff | — | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5$16.40
- Nemotron 3.5 Lightning 30B A3B$0.90
- Qwen3.5 397B-A17B$13.20
Which should you choose?
Which is better: GLM-5, Nemotron 3.5 Lightning 30B A3B or Qwen3.5 397B-A17B?
Nemotron 3.5 Lightning 30B A3B is the better all-round choice, scoring 71/100 against Qwen3.5 397B-A17B (56) and GLM-5 (37). It leads on price. Qwen3.5 397B-A17B wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GLM-5, Nemotron 3.5 Lightning 30B A3B or Qwen3.5 397B-A17B?
Nemotron 3.5 Lightning 30B A3B is cheaper at $0.05 input / $0.20 output per million tokens (median across 9 API providers; free on Nvidia). Qwen3.5 397B-A17B costs $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). At a typical mix of three input tokens to one output token, that is $0.087 per million tokens for Nemotron 3.5 Lightning 30B A3B versus $1.35 for Qwen3.5 397B-A17B (15× as much) and $1.55 for GLM-5 (18× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-5 has an ECI of 145.8, Nemotron 3.5 Lightning 30B A3B has not been scored yet and Qwen3.5 397B-A17B has an ECI of 146.7.
Which is better for coding?
There are no published SWE-bench Verified results for Nemotron 3.5 Lightning 30B A3B and Qwen3.5 397B-A17B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Nemotron 3.5 Lightning 30B A3B and Qwen3.5 397B-A17B have the largest context windows (262,144 and 262,144 tokens), against 204,800 for GLM-5. Maximum output per response: GLM-5 up to 131,072, Nemotron 3.5 Lightning 30B A3B up to 262,144, Qwen3.5 397B-A17B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GLM-5 accepts text; Nemotron 3.5 Lightning 30B A3B accepts text; Qwen3.5 397B-A17B accepts text, images, audio and video. Qwen3.5 397B-A17B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Nemotron 3.5 Lightning 30B A3B is the newest, released Aug 11, 2026. Qwen3.5 397B-A17B came out Feb 15, 2026; GLM-5 came out Feb 12, 2026.
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.
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