ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Qwen3.5 397B-A17B vs Grok 4.3 vs GLM-5

Too close to call on our weighted score (Grok 4.3 67, Qwen3.5 397B-A17B 65, GLM-5 55). The right pick depends on what you value most.

  1. 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. xAI

    Grok 4.3

    Released Apr 17, 2026

    67/100
    • ECI149.2
    • Price$1.25 / $2.50
    • Context1M
    Full specs Remove Grok 4.3

  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

Too close to call

It is close. Our weighted score puts them within 2 points (Grok 4.3 67/100, Qwen3.5 397B-A17B 65/100, GLM-5 55/100), so choose by what matters most for your work: Grok 4.3 for raw capability and Qwen3.5 397B-A17B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGrok 4.3Capabilities Index (ECI): Grok 4.3 149.2 · Qwen3.5 397B-A17B 146.7 · GLM-5 145.8
  • Lowest priceQwen3.5 397B-A17BQwen3.5 397B-A17B $1.35 · GLM-5 $1.55 · Grok 4.3 $1.56 per 1M tokens (3:1 blend)
  • Longest contextGrok 4.3Grok 4.3 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 · Grok 4.3: Text, Images, PDFs · GLM-5: Text
  • Self-hostingQwen3.5 397B-A17B and GLM-5Publishes downloadable weights
How the score is built
MeasureWeightQwen3.5 397B-A17BGrok 4.3GLM-5
CapabilityCapabilities Index (ECI)50%747773
Price25%444141
Inputs & features15%908035
Context window10%376032
Overall100%65/10067/10055/100
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 Grok 4.3 vs GLM-5 specifications side by side
SpecificationQwen3.5 397B-A17BAlibaba (Qwen)Grok 4.3xAIGLM-5Z.ai (Zhipu)
Capability
Capabilities Index (ECI)146.7149.2 (best)145.8
ECI rank#67 of 148#55 of 148 (best)#74 of 148
GPQA DiamondGraduate-level science questions86.4%88.8% (best)87.8%
FrontierMath Tiers 1–3Research-level mathematics31.2%42.8% (best)—
OTIS Mock AIME 2024–2025Competition mathematics88.9%93.3% (best)80.0%
SWE-bench VerifiedFixing real GitHub issues——72.1%
SimpleQA VerifiedShort factual questions—33.2%—
Price per million tokens
Input$0.60 (best)$1.25$1.00
Output$3.60$2.50 (best)$3.20
Cached input—$0.20$0.20
Blended (3:1)$1.35 (best)$1.56$1.55
Long-context rateSame rateOver 200K: $2.50 / $5.00Same rate
Price sourceOfficial Alibaba APIOfficial xAI APIOfficial Z.AI API
Limits
Context window262,144 tokens1,000,000 tokens (best)204,800 tokens
Max output65,536 tokens30,000 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesNo
PDFsNoYesNo
AudioYesNoNo
VideoYesNoNo
ReasoningYesYeslow · medium · highYes
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsOpenProprietaryOpen
API model IDqwen3.5-397b-a17bgrok-4.3glm-5
API providers2327 (best)27 (best)
ReleasedFeb 15, 2026Apr 17, 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
  • Grok 4.3$17.50
  • GLM-5$16.40
04 — Questions

Which should you choose?

Which is better: Qwen3.5 397B-A17B, Grok 4.3 or GLM-5?

It is close. Our weighted score puts them within 2 points (Grok 4.3 67/100, Qwen3.5 397B-A17B 65/100, GLM-5 55/100), so choose by what matters most for your work: Grok 4.3 for raw capability and Qwen3.5 397B-A17B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen3.5 397B-A17B, Grok 4.3 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); Grok 4.3 costs $1.25 input / $2.50 output per million tokens (official xAI 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 $1.56 for Grok 4.3 (1.2× as much).

Which scores higher on benchmarks?

Grok 4.3 scores higher on the Capabilities Index (ECI): Grok 4.3 149.2 (#55 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 (147.6–150.8 vs 144.8–148.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Grok 4.3 88.8%, GLM-5 87.8%, Qwen3.5 397B-A17B 86.4%; OTIS Mock AIME 2024–2025 — Grok 4.3 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 and Grok 4.3 yet, so there is no like-for-like coding score. On overall capability, Grok 4.3 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?

Grok 4.3 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, Grok 4.3 up to 30,000, 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; Grok 4.3 accepts text, images and PDFs; GLM-5 accepts text. Qwen3.5 397B-A17B handles the widest range of inputs.

Are any of these open source?

Qwen3.5 397B-A17B and GLM-5 publishes its weights and can be self-hosted; Grok 4.3 is proprietary.

Which is newer?

Grok 4.3 is the newest, released Apr 17, 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

Related comparisons