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Comparison · 3 models · Updated Oct 4, 2026

Jamba Large vs Qwen3-Coder 480B-A35B Instruct vs GPT-5 Chat

GPT-5 Chat comes out ahead, 34 to 30 and 28 on our weighted score, though Qwen3-Coder 480B-A35B Instruct is 13% cheaper per token.

  1. AI21 Labs

    Jamba Large

    Released Jul 1, 2025

    30/100
    • ECI—
    • Price$2.00 / $8.00
    • Context256K
    Full specs Remove Jamba Large

  2. Alibaba (Qwen)

    Qwen3-Coder 480B-A35B Instruct

    Released Apr 2025

    28/100
    • ECI—
    • Price$1.50 / $7.50
    • Context262K
    Full specs Remove Qwen3-Coder 480B-A35B Instruct
  3. Our pick

    OpenAI

    GPT-5 Chat

    Released Aug 7, 2025

    34/100
    • ECI—
    • Price$1.25 / $10.00
    • Context400K
    Full specs Remove GPT-5 Chat
01 — Verdict

GPT-5 Chat is our pick

GPT-5 Chat is the better all-round choice, scoring 34/100 against Jamba Large (30) and Qwen3-Coder 480B-A35B Instruct (28). It leads on inputs & features and context window. Qwen3-Coder 480B-A35B Instruct wins on price. 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 priceQwen3-Coder 480B-A35B InstructQwen3-Coder 480B-A35B Instruct $3.00 · GPT-5 Chat $3.44 · Jamba Large $3.50 per 1M tokens (3:1 blend)
  • Longest contextGPT-5 ChatGPT-5 Chat 400,000 · Qwen3-Coder 480B-A35B Instruct 262,144 · Jamba Large 256,000 tokens
  • Widest inputsGPT-5 ChatJamba Large: Text · Qwen3-Coder 480B-A35B Instruct: Text · GPT-5 Chat: Text, Images
  • Self-hostingJamba Large and Qwen3-Coder 480B-A35B InstructPublishes downloadable weights
How the score is built
MeasureWeightJamba LargeQwen3-Coder 480B-A35B InstructGPT-5 Chat
Price50%242724
Inputs & features30%352545
Context window20%363744
Overall100%30/10028/10034/100

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 Qwen3-Coder 480B-A35B Instruct vs GPT-5 Chat specifications side by side
SpecificationJamba LargeAI21 LabsQwen3-Coder 480B-A35B InstructAlibaba (Qwen)GPT-5 ChatOpenAI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$2.00$1.50$1.25 (best)
Output$8.00$7.50 (best)$10.00
Cached input———
Blended (3:1)$3.50$3.00 (best)$3.44
Long-context rateSame rateOver 32K: $2.70 / $13.50Same rate
Price sourceOfficial AI21 Labs APIOfficial Alibaba APIMedian of 2 providers
Limits
Context window256,000 tokens262,144 tokens400,000 tokens (best)
Max output4,096 tokens65,536 tokens128,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoYes
Tool callingYesYesNo
Structured outputYesNoYes
Availability
WeightsOpenOpenProprietary
API model IDjamba-largeqwen3-coder-480b-a35b-instruct—
API providers17 (best)2
ReleasedJul 1, 2025Apr 2025Aug 7, 2025
Knowledge cutoffAug 22, 2024Apr 2025Sep 30, 2024
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
  • Qwen3-Coder 480B-A35B Instruct$30.00
  • GPT-5 Chat$32.50
04 — Questions

Which should you choose?

Which is better: Jamba Large, Qwen3-Coder 480B-A35B Instruct or GPT-5 Chat?

GPT-5 Chat is the better all-round choice, scoring 34/100 against Jamba Large (30) and Qwen3-Coder 480B-A35B Instruct (28). It leads on inputs & features and context window. Qwen3-Coder 480B-A35B Instruct wins on price. 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, Qwen3-Coder 480B-A35B Instruct or GPT-5 Chat?

Qwen3-Coder 480B-A35B Instruct is cheaper at $1.50 input / $7.50 output per million tokens (official Alibaba API price). GPT-5 Chat costs $1.25 input / $10.00 output per million tokens (median across 2 API providers); 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 $3.00 per million tokens for Qwen3-Coder 480B-A35B Instruct versus $3.44 for GPT-5 Chat (1.1× as much) and $3.50 for Jamba Large (1.2× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Jamba Large has not been scored yet, Qwen3-Coder 480B-A35B Instruct has not been scored yet and GPT-5 Chat has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Jamba Large, Qwen3-Coder 480B-A35B Instruct and GPT-5 Chat yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that GPT-5 Chat does not support tool calling, which most coding agents need.

Which has the bigger context window?

GPT-5 Chat has the largest context window at 400,000 tokens, against 262,144 for Qwen3-Coder 480B-A35B Instruct and 256,000 for Jamba Large. Maximum output per response: Jamba Large up to 4,096, Qwen3-Coder 480B-A35B Instruct up to 65,536, GPT-5 Chat up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Jamba Large accepts text; Qwen3-Coder 480B-A35B Instruct accepts text; GPT-5 Chat accepts text and images. GPT-5 Chat handles the widest range of inputs.

Are any of these open source?

Jamba Large and Qwen3-Coder 480B-A35B Instruct publishes its weights and can be self-hosted; GPT-5 Chat is proprietary.

Which is newer?

GPT-5 Chat is the newest, released Aug 7, 2025. Jamba Large came out Jul 1, 2025; Qwen3-Coder 480B-A35B Instruct came out Apr 2025. Knowledge cutoff: Jamba Large Aug 22, 2024, Qwen3-Coder 480B-A35B Instruct Apr 2025, GPT-5 Chat Sep 30, 2024.

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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