ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GLM-5 vs Nemotron 3 Ultra 550B A55B vs Qwen3.5 397B-A17B

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.

  1. Z.ai (Zhipu)

    GLM-5

    Released Feb 12, 2026

    55/100
    • ECI145.8
    • Price$1.00 / $3.20
    • Context205K
  2. NVIDIA

    Nemotron 3 Ultra 550B A55B

    Released Jun 4, 2026

    62/100
    • ECI146.2
    • Price$0.50 / $2.50
    • Context1M
  3. Our pick

    Alibaba (Qwen)

    Qwen3.5 397B-A17B

    Released Feb 15, 2026

    65/100
    • ECI146.7
    • Price$0.60 / $3.60
    • Context262K
01 — Verdict

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-A17BGLM-5: Text · Nemotron 3 Ultra 550B A55B: Text · Qwen3.5 397B-A17B: Text, Images, Audio, Video
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGLM-5Nemotron 3 Ultra 550B A55BQwen3.5 397B-A17B
CapabilityCapabilities Index (ECI)50%737374
Price25%415044
Inputs & features15%354590
Context window10%326037
Overall100%55/10062/10065/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

GLM-5 vs Nemotron 3 Ultra 550B A55B vs Qwen3.5 397B-A17B specifications side by side
SpecificationGLM-5Z.ai (Zhipu)Nemotron 3 Ultra 550B A55BNVIDIAQwen3.5 397B-A17BAlibaba (Qwen)
Capability
Capabilities Index (ECI)145.8146.2146.7 (best)
ECI rank#74 of 148#70 of 148#67 of 148 (best)
GPQA DiamondGraduate-level science questions87.8% (best)85.4%86.4%
FrontierMath Tiers 1–3Research-level mathematics——31.2%
OTIS Mock AIME 2024–2025Competition mathematics80.0%86.7%88.9% (best)
SWE-bench VerifiedFixing real GitHub issues72.1%——
Price per million tokens
Input$1.00$0.50 (best)$0.60
Output$3.20$2.50 (best)$3.60
Cached input$0.20$0.15 (best)—
Blended (3:1)$1.55$1.00 (best)$1.35
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Z.AI APIOfficial Nvidia APIOfficial Alibaba API
Limits
Context window204,800 tokens1,000,000 tokens (best)262,144 tokens
Max output131,072 tokens (best)128,000 tokens65,536 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoYes
VideoNoNoYes
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoYesYes
Availability
WeightsOpenOpenOpen
API model IDglm-5nvidia/nemotron-3-ultra-550b-a55bqwen3.5-397b-a17b
API providers27 (best)2123
ReleasedFeb 12, 2026Jun 4, 2026Feb 15, 2026
Knowledge cutoff———
03 — Cost

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 Ultra 550B A55B$10.00
  • Qwen3.5 397B-A17B$13.20
04 — Questions

Which should you choose?

Which is better: GLM-5, Nemotron 3 Ultra 550B A55B or Qwen3.5 397B-A17B?

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, GLM-5, Nemotron 3 Ultra 550B A55B or Qwen3.5 397B-A17B?

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 Nemotron 3 Ultra 550B A55B and Qwen3.5 397B-A17B 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: GLM-5 up to 131,072, Nemotron 3 Ultra 550B A55B up to 128,000, Qwen3.5 397B-A17B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

GLM-5 accepts text; Nemotron 3 Ultra 550B A55B 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 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.