ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Qwen3.6 27B vs Nemotron 3 Ultra 550B A55B vs GLM-5

Qwen3.6 27B comes out ahead, 65 to 62 and 55 on our weighted score, though Nemotron 3 Ultra 550B A55B is 26% cheaper per token.

  1. Our pick

    Alibaba (Qwen)

    Qwen3.6 27B

    Released Apr 22, 2026

    65/100
    • ECI146.5
    • Price$0.60 / $3.60
    • Context262K
  2. NVIDIA

    Nemotron 3 Ultra 550B A55B

    Released Jun 4, 2026

    62/100
    • ECI146.2
    • Price$0.50 / $2.50
    • Context1M
  3. Z.ai (Zhipu)

    GLM-5

    Released Feb 12, 2026

    55/100
    • ECI145.8
    • Price$1.00 / $3.20
    • Context205K
01 — Verdict

Qwen3.6 27B is our pick

Qwen3.6 27B 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%.

  • CapabilityQwen3.6 27BCapabilities Index (ECI): Qwen3.6 27B 146.5 · Nemotron 3 Ultra 550B A55B 146.2 · GLM-5 145.8
  • Lowest priceNemotron 3 Ultra 550B A55BNemotron 3 Ultra 550B A55B $1.00 · Qwen3.6 27B $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 · Qwen3.6 27B 262,144 · GLM-5 204,800 tokens
  • Widest inputsQwen3.6 27BQwen3.6 27B: 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
How the score is built
MeasureWeightQwen3.6 27BNemotron 3 Ultra 550B A55BGLM-5
CapabilityCapabilities Index (ECI)50%747373
Price25%445041
Inputs & features15%904535
Context window10%376032
Overall100%65/10062/10055/100
02 — Side by side

Every spec in one table

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

Qwen3.6 27B vs Nemotron 3 Ultra 550B A55B vs GLM-5 specifications side by side
SpecificationQwen3.6 27BAlibaba (Qwen)Nemotron 3 Ultra 550B A55BNVIDIAGLM-5Z.ai (Zhipu)
Capability
Capabilities Index (ECI)146.5 (best)146.2145.8
ECI rank#68 of 148 (best)#70 of 148#74 of 148
GPQA DiamondGraduate-level science questions85.9%85.4%87.8% (best)
FrontierMath Tiers 1–3Research-level mathematics35.1%——
OTIS Mock AIME 2024–2025Competition mathematics91.1% (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 rateSame rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial Nvidia APIOfficial Z.AI API
Limits
Context window262,144 tokens1,000,000 tokens (best)204,800 tokens
Max output65,536 tokens128,000 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsNoNoNo
AudioYesNoNo
VideoYesNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsOpenOpenOpen
API model IDqwen3.6-27bnvidia/nemotron-3-ultra-550b-a55bglm-5
API providers27 (best)2127 (best)
ReleasedApr 22, 2026Jun 4, 2026Feb 12, 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.

  • Qwen3.6 27B$13.20
  • Nemotron 3 Ultra 550B A55B$10.00
  • GLM-5$16.40
04 — Questions

Which should you choose?

Which is better: Qwen3.6 27B, Nemotron 3 Ultra 550B A55B or GLM-5?

Qwen3.6 27B 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, Qwen3.6 27B, 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). Qwen3.6 27B 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 Qwen3.6 27B (1.4× as much) and $1.55 for GLM-5 (1.6× as much).

Which scores higher on benchmarks?

Qwen3.6 27B scores higher on the Capabilities Index (ECI): Qwen3.6 27B 146.5 (#68 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 (144.2–147.9 vs 143.9–148.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5 87.8%, Qwen3.6 27B 85.9%, Nemotron 3 Ultra 550B A55B 85.4%; OTIS Mock AIME 2024–2025 — Qwen3.6 27B 91.1%, 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 Qwen3.6 27B and Nemotron 3 Ultra 550B A55B yet, so there is no like-for-like coding score. On overall capability, Qwen3.6 27B 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 Qwen3.6 27B and 204,800 for GLM-5. Maximum output per response: Qwen3.6 27B 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?

Qwen3.6 27B accepts text, images, audio and video; Nemotron 3 Ultra 550B A55B accepts text; GLM-5 accepts text. Qwen3.6 27B 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. Qwen3.6 27B came out Apr 22, 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.