ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Qwen3.5 397B-A17B vs GLM-5.1 vs GLM-5

Qwen3.5 397B-A17B comes out ahead, 65 to 57 and 55 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Alibaba (Qwen)

    Qwen3.5 397B-A17B

    Released Feb 15, 2026

    65/100
    • ECI146.7
    • Price$0.60 / $3.60
    • Context262K
    Full specs Remove Qwen3.5 397B-A17B

  2. Z.ai (Zhipu)

    GLM-5.1

    Released Apr 7, 2026

    57/100
    • ECI149.9
    • Price$1.40 / $4.40
    • Context200K
    Full specs Remove GLM-5.1

  3. Z.ai (Zhipu)

    GLM-5

    Released Feb 12, 2026

    55/100
    • ECI145.8
    • Price$1.00 / $3.20
    • Context205K
    Full specs Remove GLM-5
01 — Verdict

Qwen3.5 397B-A17B is our pick

Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against GLM-5.1 (57) and GLM-5 (55). It leads on price, inputs & features and context window. GLM-5.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGLM-5.1Capabilities Index (ECI): GLM-5.1 149.9 · Qwen3.5 397B-A17B 146.7 · GLM-5 145.8
  • Lowest priceQwen3.5 397B-A17BQwen3.5 397B-A17B $1.35 · GLM-5 $1.55 · GLM-5.1 $2.15 per 1M tokens (3:1 blend)
  • Longest contextQwen3.5 397B-A17BQwen3.5 397B-A17B 262,144 · GLM-5 204,800 · GLM-5.1 200,000 tokens
  • Widest inputsQwen3.5 397B-A17BQwen3.5 397B-A17B: Text, Images, Audio, Video · GLM-5.1: Text · GLM-5: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3.5 397B-A17BGLM-5.1GLM-5
CapabilityCapabilities Index (ECI)50%747873
Price25%443441
Inputs & features15%904535
Context window10%373232
Overall100%65/10057/10055/100
02 — Side by side

Every spec in one table

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

Qwen3.5 397B-A17B vs GLM-5.1 vs GLM-5 specifications side by side
SpecificationQwen3.5 397B-A17BAlibaba (Qwen)GLM-5.1Z.ai (Zhipu)GLM-5Z.ai (Zhipu)
Capability
Capabilities Index (ECI)146.7149.9 (best)145.8
ECI rank#67 of 148#51 of 148 (best)#74 of 148
GPQA DiamondGraduate-level science questions86.4%89.9% (best)87.8%
FrontierMath Tiers 1–3Research-level mathematics31.2%36.8% (best)—
OTIS Mock AIME 2024–2025Competition mathematics88.9%93.3% (best)80.0%
SWE-bench VerifiedFixing real GitHub issues—74.2% (best)72.1%
SimpleQA VerifiedShort factual questions—34.0%—
Price per million tokens
Input$0.60 (best)$1.40$1.00
Output$3.60$4.40$3.20 (best)
Cached input—$0.26$0.20 (best)
Blended (3:1)$1.35 (best)$2.15$1.55
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial Z.AI APIOfficial Z.AI API
Limits
Context window262,144 tokens (best)200,000 tokens204,800 tokens
Max output65,536 tokens131,072 tokens (best)131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsNoNoNo
AudioYesNoNo
VideoYesNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsOpenOpenOpen
API model IDqwen3.5-397b-a17bglm-5.1glm-5
API providers2340 (best)27
ReleasedFeb 15, 2026Apr 7, 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.

  • Qwen3.5 397B-A17B$13.20
  • GLM-5.1$22.80
  • GLM-5$16.40
04 — Questions

Which should you choose?

Which is better: Qwen3.5 397B-A17B, GLM-5.1 or GLM-5?

Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against GLM-5.1 (57) and GLM-5 (55). It leads on price, inputs & features and context window. GLM-5.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen3.5 397B-A17B, GLM-5.1 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); GLM-5.1 costs $1.40 input / $4.40 output per million tokens (official Z.AI 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 $2.15 for GLM-5.1 (1.6× as much).

Which scores higher on benchmarks?

GLM-5.1 scores higher on the Capabilities Index (ECI): GLM-5.1 149.9 (#51 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 (148.0–151.6 vs 144.8–148.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5.1 89.9%, GLM-5 87.8%, Qwen3.5 397B-A17B 86.4%; OTIS Mock AIME 2024–2025 — GLM-5.1 93.3%, Qwen3.5 397B-A17B 88.9%, 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, GLM-5.1 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 GLM-5.1. Maximum output per response: Qwen3.5 397B-A17B up to 65,536, GLM-5.1 up to 131,072, 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; GLM-5.1 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?

GLM-5.1 is the newest, released Apr 7, 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.

05 — Keep comparing

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