AI Models · Open-Source vs Paid

Jamba Large 1.7 Open vs GPT-4 Paid

Jamba Large 1.7 vs GPT-4 compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.

GPT-4 — full profile ›

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

Choose Jamba Large 1.7 if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose GPT-4 if you want frontier capability through a managed API with zero infrastructure to run.

Jamba Large 1.7 vs GPT-4 specs

SpecJamba Large 1.7GPT-4
MakerAi21OpenAI
TypeOpen-weightProprietary
Context window256K tokens8K tokens
Input price$2/M · free self-host$30/M
Output price$8/M · free self-host$60/M
Vision / multimodalNoNo
Tool / function callingYesYes
Self-hostableYesNo (API only)
LicenseOpen weightsProprietary

Feature comparison

CapabilityJamba Large 1.7GPT-4
Open weights (downloadable)✓✗
Self-hostable✓✗
Runs fully offline✓✗
Vision / multimodal✗✗
Tool / function calling✓✓
1M+ context window✗✗

Benchmarks: Jamba Large 1.7 vs GPT-4

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

Jamba Large 1.7 delivers 7.5× more intelligence per dollar.
Jamba Large 1.7
GPT-4
Intelligence index
5.3
7
Math index
2.3
–
GPQA
39%
–
MMLU-Pro
57.7%
–
Humanity's Last Exam
3.8%
–
Long Context Reasoning
17.3%
–
LiveCodeBench
18.1%
–
SciCode
18.8%
–
MATH-500
60%
–
AIME
5.7%
–
AIME 2025
2.3%
–
IFBench
35.2%
–
τ²-Bench
13.5%
–
Terminal-Bench Hard
2.3%
–
Coding index
–
13.1
Speed
56.4 tok/s
0 tok/s
Latency
0.87s
0s
Intelligence per $
1.5
0.2

Benchmark data by Artificial Analysis.

How Jamba Large 1.7 and GPT-4 score

🏆 Best value & openness: Jamba Large 1.7 (4.2 vs 2.0 / 5)
CriterionJamba Large 1.7GPT-4
Cost-efficiency3.52.0
Context window4.02.0
Openness5.01.5
Self-hosting5.01.0
Multimodality3.53.5

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

Jamba Large 1.7 Open

Ai21 · Open-weight

Jamba Large 1.7 is the latest model in the Jamba open family, offering improvements in grounding, instruction-following, and overall efficiency. Built on a hybrid SSM-Transformer architecture with a 256K context...

GPT-4 Paid

OpenAI · Proprietary

OpenAI's flagship model, GPT-4 is a large-scale multimodal language model capable of solving difficult problems with greater accuracy than previous models due to its broader general knowledge and advanced reasoning...

Frequently asked questions

Is Jamba Large 1.7 as good as GPT-4?

Jamba Large 1.7 is open-weight and competitive on many tasks, but GPT-4 may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.

Can I run Jamba Large 1.7 locally?

Yes. Jamba Large 1.7 has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. GPT-4 is API-only and cannot be self-hosted.

How much cheaper is Jamba Large 1.7?

Jamba Large 1.7 costs $8/M output vs $60/M for GPT-4 — roughly 8x cheaper via API, and free if you self-host.

Jamba Large 1.7 vs GPT-4 — which should I pick in 2026?

Choose Jamba Large 1.7 if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose GPT-4 if you want frontier capability through a managed API with zero infrastructure to run.

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