Qwen3.5 397B-A17B vs Nemotron 3 Ultra 550B A55B vs GLM-5
Qwen3.5 397B-A17B comes out ahead, 65 to 62 and 55 on our weighted score, though Nemotron 3 Ultra 550B A55B is 26% cheaper per token.
- Our pick
Alibaba (Qwen)Qwen3.5 397B-A17B
65/100- ECI146.7
- Price$0.60 / $3.60
- Context262K
NVIDIANemotron 3 Ultra 550B A55B
62/100- ECI146.2
- Price$0.50 / $2.50
- Context1M
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 Nemotron 3 Ultra 550B A55B (62) and GLM-5 (55). It leads on inputs & features. Nemotron 3 Ultra 550B A55B wins on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.5 397B-A17BCapabilities Index (ECI): Qwen3.5 397B-A17B 146.7 · Nemotron 3 Ultra 550B A55B 146.2 · GLM-5 145.8
- Lowest priceNemotron 3 Ultra 550B A55BNemotron 3 Ultra 550B A55B $1.00 · Qwen3.5 397B-A17B $1.35 · GLM-5 $1.55 per 1M tokens (3:1 blend)
- Longest contextNemotron 3 Ultra 550B A55BNemotron 3 Ultra 550B A55B 1,000,000 · Qwen3.5 397B-A17B 262,144 · GLM-5 204,800 tokens
- Widest inputsQwen3.5 397B-A17BQwen3.5 397B-A17B: Text, Images, Audio, Video · Nemotron 3 Ultra 550B A55B: Text · GLM-5: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3.5 397B-A17B | Nemotron 3 Ultra 550B A55B | GLM-5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 74 | 73 | 73 |
| Price | 25% | 44 | 50 | 41 |
| Inputs & features | 15% | 90 | 45 | 35 |
| Context window | 10% | 37 | 60 | 32 |
| Overall | 100% | 65/100 | 62/100 | 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) | Nemotron 3 Ultra 550B A55BNVIDIA | GLM-5Z.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 146.7 (best) | 146.2 | 145.8 |
| ECI rank | #67 of 148 (best) | #70 of 148 | #74 of 148 |
| GPQA DiamondGraduate-level science questions | 86.4% | 85.4% | 87.8% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 31.2% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 88.9% (best) | 86.7% | 80.0% |
| SWE-bench VerifiedFixing real GitHub issues | — | — | 72.1% |
| Price per million tokens | |||
| Input | $0.60 | $0.50 (best) | $1.00 |
| Output | $3.60 | $2.50 (best) | $3.20 |
| Cached input | — | $0.15 (best) | $0.20 |
| Blended (3:1) | $1.35 | $1.00 (best) | $1.55 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Nvidia API | Official Z.AI API |
| Limits | |||
| Context window | 262,144 tokens | 1,000,000 tokens (best) | 204,800 tokens |
| Max output | 65,536 tokens | 128,000 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | qwen3.5-397b-a17b | nvidia/nemotron-3-ultra-550b-a55b | glm-5 |
| API providers | 23 | 21 | 27 (best) |
| Released | Feb 15, 2026 | Jun 4, 2026 | Feb 12, 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.
- Qwen3.5 397B-A17B$13.20
- Nemotron 3 Ultra 550B A55B$10.00
- GLM-5$16.40
Which should you choose?
Which is better: Qwen3.5 397B-A17B, Nemotron 3 Ultra 550B A55B or GLM-5?
Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against Nemotron 3 Ultra 550B A55B (62) and GLM-5 (55). It leads on inputs & features. Nemotron 3 Ultra 550B A55B wins on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3.5 397B-A17B, Nemotron 3 Ultra 550B A55B or GLM-5?
Nemotron 3 Ultra 550B A55B is cheaper at $0.50 input / $2.50 output per million tokens (official Nvidia API price). 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 $1.00 per million tokens for Nemotron 3 Ultra 550B A55B versus $1.35 for Qwen3.5 397B-A17B (1.4× as much) and $1.55 for GLM-5 (1.6× as much).
Which scores higher on benchmarks?
Qwen3.5 397B-A17B scores higher on the Capabilities Index (ECI): Qwen3.5 397B-A17B 146.7 (#67 of 148), Nemotron 3 Ultra 550B A55B 146.2 (#70 of 148) and GLM-5 145.8 (#74 of 148). The confidence ranges of the top two overlap (144.8–148.2 vs 143.9–148.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5 87.8%, Qwen3.5 397B-A17B 86.4%, Nemotron 3 Ultra 550B A55B 85.4%; OTIS Mock AIME 2024–2025 — Qwen3.5 397B-A17B 88.9%, Nemotron 3 Ultra 550B A55B 86.7%, GLM-5 80.0%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 397B-A17B and Nemotron 3 Ultra 550B A55B yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 397B-A17B 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?
Nemotron 3 Ultra 550B A55B has the largest context window at 1,000,000 tokens, against 262,144 for Qwen3.5 397B-A17B and 204,800 for GLM-5. Maximum output per response: Qwen3.5 397B-A17B up to 65,536, Nemotron 3 Ultra 550B A55B up to 128,000, 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; Nemotron 3 Ultra 550B A55B accepts text; GLM-5 accepts text. 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 Ultra 550B A55B is the newest, released Jun 4, 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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