ZMIME
Comparison · 2 models · Updated Nov 2, 2026

Jamba Large vs GLM-4.7

GLM-4.7 comes out ahead, 41 to 29 on our weighted score, and it is the cheaper option too.

  1. AI21 Labs

    Jamba Large

    Released Jul 3, 2025

    29/100
    • ECI—
    • Price$2.00 / $8.00
    • Context256K
    Full specs Remove Jamba Large
  2. Our pick

    Z.ai (Zhipu)

    GLM-4.7

    Released Dec 22, 2025

    41/100
    • ECI143.7
    • Price$0.60 / $2.20
    • Context205K
    Full specs Remove GLM-4.7

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

GLM-4.7 is our pick

GLM-4.7 is the better all-round choice, scoring 41/100 against Jamba Large (29). It leads on price. Jamba Large wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceGLM-4.7GLM-4.7 $1.00 · Jamba Large $3.50 per 1M tokens (3:1 blend)
  • Longest contextJamba LargeJamba Large 256,000 · GLM-4.7 204,800 tokens
  • Widest inputsSame inputsJamba Large: Text · GLM-4.7: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightJamba LargeGLM-4.7
Price50%2348
Inputs & features30%3535
Context window20%3632
Overall100%29/10041/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

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

Jamba Large vs GLM-4.7 specifications side by side
SpecificationJamba LargeAI21 LabsGLM-4.7Z.ai (Zhipu)
Capability
Capabilities Index (ECI)—143.7
ECI rank—#94 of 165
GPQA DiamondGraduate-level science questions—83.3%
OTIS Mock AIME 2024–2025Competition mathematics—83.3%
SimpleQA VerifiedShort factual questions—32.2%
Price per million tokens
Input$2.00$0.60 (best)
Output$8.00$2.20 (best)
Cached input—$0.11
Blended (3:1)$3.50$1.00 (best)
Long-context rateSame rateSame rate
Price sourceOfficial AI21 Labs APIOfficial Z.AI API
Limits
Context window256,000 tokens (best)204,800 tokens
Max output4,096 tokens131,072 tokens (best)
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoYes
Tool callingYesYes
Structured outputYesNo
Availability
WeightsOpenOpen
API model IDjamba-largeglm-4.7
API providers131 (best)
ReleasedJul 3, 2025Dec 22, 2025
Knowledge cutoffAug 22, 2024Apr 2025
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.

  • Jamba Large$36.00
  • GLM-4.7$10.40
04 — Questions

Which should you choose?

Which is better: Jamba Large or GLM-4.7?

GLM-4.7 is the better all-round choice, scoring 41/100 against Jamba Large (29). It leads on price. Jamba Large wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Jamba Large or GLM-4.7?

GLM-4.7 is cheaper at $0.60 input / $2.20 output per million tokens (official Z.AI API price). Jamba Large costs $2.00 input / $8.00 output per million tokens (official AI21 Labs API price). At a typical mix of three input tokens to one output token, that is $1.00 per million tokens for GLM-4.7 versus $3.50 for Jamba Large (3.5× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Jamba Large has not been scored yet and GLM-4.7 has an ECI of 143.7.

Which is better for coding?

There are no published SWE-bench Verified results for Jamba Large and GLM-4.7 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

Jamba Large has the largest context window at 256,000 tokens, against 204,800 for GLM-4.7. Maximum output per response: Jamba Large up to 4,096, GLM-4.7 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Jamba Large accepts text; GLM-4.7 accepts text. They handle the same number of input types.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

GLM-4.7 is the newest, released Dec 22, 2025. Jamba Large came out Jul 3, 2025. Knowledge cutoff: Jamba Large Aug 22, 2024, GLM-4.7 Apr 2025.

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 Nov 2, 2026.

05 — Keep comparing

Related comparisons